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

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

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

Circulating levels of novel adipocytokines in patients with colorectal cancer

Objective: Adipocytokines have been reported to contribute to the pathogenesis of colorectal cancer (CRC). The aim of this matched case-control study was to explore circulating novel adipocytokines, such as serum visfatin, omentin-1 and vaspin levels in patients with CRC. Method: Serum visfatin, omentin-1, and vaspin levels were measured in 69 subjects (39 patients with colorectal cancer and 30 age- and sex-matched healthy controls) using enzyme-linked immunosorbent assay (ELISA) methods. Results: Compared with the controls, patients with CRC had significantly higher circulating omentin-1 (203.23 vs 9.12 ng/ml, p < 0.0001) visfatin (4.03 vs 2.01 ng/ml, p < 0.0001) and vaspin (0.54 vs 0.31 ng/ ml, p = 0.015) levels. After adjustment for covariates (age and body mass index), patients with CRC had significantly higher serum omentin-1 (p < 0.0001), visfatin (p < 0.0001), and vaspin (p = 0.040) levels than the control group. Furthermore, the results did not change when age and waist-to-hip ratio were considered as covariates in the general linear models. Conclusions: The observed higher levels of omentin-1, visfatin, and vaspin in patients with CRC, independent of measures of obesity, suggest that these adipocytokines may have a potential role in the development of CRC through mechanisms other than the indirect mechanisms that are active in the association between obesity and CRC

Circulating levels of novel adipocytokines in patients with colorectal cancer

Objective: Adipocytokines have been reported to contribute to the pathogenesis of colorectal cancer (CRC). The aim of this matched case-control study was to explore circulating novel adipocytokines, such as serum visfatin, omentin-1 and vaspin levels in patients with CRC. Method: Serum visfatin, omentin-1, and vaspin levels were measured in 69 subjects (39 patients with colorectal cancer and 30 age- and sex-matched healthy controls) using enzyme-linked immunosorbent assay (ELISA) methods. Results: Compared with the controls, patients with CRC had significantly higher circulating omentin-1 (203.23 vs 9.12 ng/ml, p < 0.0001) visfatin (4.03 vs 2.01 ng/ml, p < 0.0001) and vaspin (0.54 vs 0.31 ng/ ml, p = 0.015) levels. After adjustment for covariates (age and body mass index), patients with CRC had significantly higher serum omentin-1 (p < 0.0001), visfatin (p < 0.0001), and vaspin (p = 0.040) levels than the control group. Furthermore, the results did not change when age and waist-to-hip ratio were considered as covariates in the general linear models. Conclusions: The observed higher levels of omentin-1, visfatin, and vaspin in patients with CRC, independent of measures of obesity, suggest that these adipocytokines may have a potential role in the development of CRC through mechanisms other than the indirect mechanisms that are active in the association between obesity and CRC

An order acceptance using FAHP and TOPSIS methods: A case study of Iranian vehicle belt production industry

Decisions related to acceptance or rejection of orders play an important role in companies engaged in make-to-order production. The incoming orders have a specific delivery date by which the customer expects the due date to be met and the order delivered. In some cases the level of input orders exceeds beyond the existing capacity. In such situations the main concern is to decide which orders must be accepted and which ones rejected taking into account the available production capacity. This paper prioritises the input orders according to a comprehensive and systematic multi criteria decision making (MCDM) model. It then proceeds with making decisions to either accept or reject orders according to the calculated prioritises and production constraints. Ultimately the optimum list of orders for acceptance is determined. The proposed model is a combination of two techniques of Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this model FAHP is used to determine the weights of criteria and TOPSIS is used for prioritizing the orders. Finally the proposed model is tested for its efficiency by application to a real case

Agent-Based Simulation Consumer Behavior in Impulse Buying

Because of the dissemination of impulse buying behavior in consumers its academic studies have increased over the last decade. Because in large stores, sales have to be increased, the behavior of consumers in impulse buying to be taken into account by the researchers and managers of the stores. The purpose of this paper is agent–based simulation impulse buying behavior consumer (customers) considering the discount, the optimal time of customer presence in stores from the point of view the store managers and learning from previous buying. The population and the statistical sample of the present study include 15 academic professors who are expert in impulse buying and marketing topics. The present study is executive in terms of purpose. It is mathematical in terms of data type and modeling method. This model examines the existing reality of consumer buying behavior to develop impulse buying models in the agent-based simulation environment by Netlogo software. After reviewing the theoretical foundations and research background 5 dimensions and seventeen indicators have been identified by fuzzy screening method. The results showed that the factors considered in this study describe the impulse buying behavior of consumers as an economic analysis based on consumer relations and customer-product relationship. This achievement by simulating customer behavior at the time of purchase strives to provide valuable information for managers shareholders and store decision makers

Efficiency evaluation of cement production companies using nonhomogeneous network DEA

Cement production in Iran takes place across various geographical locations, each characterized by distinct weather conditions. The technology employed in cement production varies depending on the availability of raw materials, fuel sources, and essential resources like water. Consequently, diverse inputs and outputs assume significance in each production technology, resulting in non-homogeneity among cement factories. Despite these differences, all these facilities are engaged in cement production, warranting a comparative analysis of their efficiency. This study examines the operational processes of five different cement production technologies—dry, semi-dry, humid, semi-humid, and wet slurry—across four companies comprising a total of nine factories. The study evaluates their efficiency between 2017 and 2020 using network data envelopment analysis under non-homogeneous conditions across three modeling stages. An important aspect of this study is its focus on the entire supply chain, from raw materials to the final product. Although the raw materials employed vary among different cement production technologies, the end product remains largely consistent.IntroductionIn certain real-world scenarios, even with similar production technologies, the assumption of homogeneous decision-making units may not hold true. Practical applications often involve supply chain structures that differ significantly from others. For instance, some supply chains may, at certain stages, eject intermediate products to meet specific needs, a phenomenon not universal to all supply chains, resulting in non-homogeneous chains. The cement industry, including Iran, constitutes one of the pivotal economic sectors. Therefore, mitigating shortcomings, including resource and material waste reduction, can have a substantial impact on this industry and consequently on the broader economy. Due to varying climatic conditions, cement production employs diverse technologies, primarily categorized as dry or wet processes. This study investigates the operational processes of five different cement production methods—dry, semi-dry, humid, semi-humid, and wet slurry—across four companies with a total of nine factories. Their performance between 2017 and 2020 is evaluated using network DEA under non-homogeneous conditions, encompassing three modeling stages.Materials and MethodsIn novel approaches, DEA is utilized to assess the performance of network decision-making units. The models typically assume homogeneity among decision-making units, which may not always align with real-world conditions. Practical situations often violate assumptions of unit homogeneity and uniformity in input and output parameters. Consequently, it is imperative to present and employ methods and models capable of accommodating non-homogeneous units. This study employs a scientific library research approach and practical purposive data collection to gather relevant information. This information informs specific adjustments to operational processes. Consequently, the development of a robust system for evaluating supply chain performance becomes essential. The study utilizes common models to evaluate efficiency under non-homogeneous conditions. Classification of operational processes and related data, followed by modeling using Lingo software, is employed in this research.Discussion and Result:This article consists of two parts. Initially, it introduces the fundamental performance evaluation model and subsequently delves into the three-stage model of data envelopment analysis (DEA) within the supply chain context. In the second part, the production processes of Portland cement are examined, covering dry, semi-dry, humid, semi-humid, and wet slurry processes. The proposed approach assesses the performance of four cement production companies over a four-year period. Efficiency calculations for nine factories are conducted in three stages:The first stage consists of three steps as follows:First step: Input and output parameters used across the entire production process are categorized based on the different production methods.Second step: Processes utilizing similar production steps, as determined in the first stage, are grouped into four categories.Third step: Efficiency assessments for factories sharing similar production stages from the previous step are conducted, resulting in the identification of nine categories.Second stage: The efficiency of each category, characterized by a common feature from the previous step, is calculated.Third stage: To determine the overall efficiency of each factory, the efficiencies of individual processes are multiplied.ConclusionsThe results indicate that the fourth cement production company exhibits the highest efficiency, while the first company has the lowest efficiency. Notably, the lowest efficiency for the years 2017 to 2020 was recorded by the first company in 2020, while the fourth company achieved the highest efficiency in the same year. Among the factories, the lowest efficiency was observed in 2017 for the first company's five semi-dry factories, the fourth company's four semi-humid factories in 2018, the fourth company's nine wet slurry factories in 2018, the third company's seven semi-humid factories in 2020, and the fourth company's four semi-humid factories in 2020, which recorded the highest efficiency. Further examination and identification of suitable solutions to enhance efficiency in cases with lower efficiency levels can follow this study