جستجوی مقالات مرتبط با کلیدواژه « discriminant Analysis » در نشریات گروه « مدیریت »

In the last decade, the most important philosophy agreed upon in organizations has been environmentalism that can help them to achieve a sustainable competitive advantage by improving their reputation and position. A very important tool for organizations to achieve this goal is to observe the importance of green management practices. The main purpose of this study is to provide a clustering and conducting a discriminant analysis of public organizations in terms of performance in green management and its components. This study is applied in terms of purpose, and regarding method and nature is a descriptive survey. The statistical population of this study consists of the public organizations of city of Bushehr, which were selected using simple random sampling method. Finally, 74 organizations were selected as sample members. A researcher-made questionnaire was used for data collection. The validity and reliability of measures were confirmed employing content analysis method and Cronbach's alpha method, respectively. In this study, nine influential components in green management were identified by studying the theoretical foundations, literature reviewing and examining the main documents. Then, collected data were analyzed by genetic algorithms, K-means and discriminant analysis. The results show that public organizations, participated in this study, are in the "action-oriented" and "reactionary" clusters from the perspective of green management, and the proposed predictive function has a very high power in distinguishing organizations. In terms of contribution, this study has clustered public organization from a new perspective.

Today, pure tools for creating and improving customer value are considered in the waste elimination process. Elimination of fundamental losses is considered to achieve economic, environmental and social sustainability. Accordingly, the purpose of this study is to discriminant analysis of supply chain stability clusters based on lean tools. In this study, data collection tools are two types of questionnaires designed to assess the stability of supply chain sustainability and assessment of lean manufacturing tools in small and medium industries of East Azerbaijan Province. To determine the validity of the questionnaires, construct validity based on factor analysis and Cronbach's alpha coefficient were used to determine their reliability. The statistical population of this study is all the small and medium industries in East Azerbaijan Province. To analyze the data, the analysis of the cluster analysis and audit analysis has been used. The results show that based on cluster analysis, firms can be grouped into three clusters, one of which is not known as stable cluster because of low scores. The results of discriminant analysis showed an audit function that shows the contribution of each of the lean tools in the separation between sustainability clusters and classified in two groups: complete and stable sustainability. It should be noted that the accuracy of this function is 98.1%.

The Mass market strategy does not have a big chance for success in a competitive market. Therefore, by segmenting a heterogeneous market into some smaller and homogenous markets in which customers have similar characteristics, it is expected that the resources can be more efficiently utilized for meeting the needs of customers. The purpose of this study  was mathematical modelling of market segmentation of an Iranian steel-making company using value proposition elements of the company for the customers. The model that mentioned above was used for the analysis of data related to six value proposition elements from 129 major customers of the company. This model was solved using the GAMS software and the number of optimized segments was 9. In this study, the results obtained were compared with those achieved by the conventional segmentation methods such as K-means and self-organized neural networks and two-step clustering. Further, for the validation of the mathematical model used, due to the multi-attribute nature of the segmentation done, discriminant analysis of research data was done after segmentation and the success percentage of the ranking rule was found to be 95.3 %.  Also, the similarity criterion was computed for each potential new customer to show which group the new customer belonged.

Major challenge in the field of customer relationship management is on customer understanding and customer-centric organizations realize optimal allocation of resources between them and rank them according to their value to the company. This paper provides a suitable model for customer segmentation، based on the customer life time The process proposed in study corporate based on the data mining method in the Crisp Six phases of design and after determining the indexes of LRFM model (Length،Recency،Frequency، Monetary) at 921 customers and weighting them AHP group according to Discriminant Analysis in 16 departments and five cluster core categories and has been determined the customer life time. The results of the present study was to analyze the characteristics of providing corporate customers. Also، customer segmentation، key customers، and the value was determined. Finally some recommendations is presented to improve the company''s customer relationship management system.

Nowadays, narcotic drugs problem is one of the most important social damages in Iran. Addiction can lead to some destructive effects in the society including economic, cultural, mental, moral and legal effects. Hence, monitoring the smuggling of narcotic drugs in Iran is inevitable and improves the community health. Distribution of the narcotic drugs can be characterized by two correlated quality characteristics including the weights of discovered narcotic drugs and the number of arrested smugglers by the police. It is assumed that the first quality characteristic is a variable and follows a normal distribution whereas the second is an attribute and follows a Poisson distribution. The positive correlation also exists between the variable and attribute quality characteristics. In this paper, two methods based on the discriminant analysis are proposed for simultaneous monitoring of correlated variable and attribute quality characteristics. The first method is based on the combination of discriminant analysis technique and artificial neural network and the second is based on the discriminant analysis technique and exponential weighted moving average (EWMA) control chart. The performance of the proposed methods in detecting different step shifts in the quality characteristics is evaluated through simulation in terms of average run length criterion. Finally, a numerical example is presented to elaborate the proposed methods. The results confirm the high performance of both methods for monitoring purpose and can be implemented by the police to monitor the distribution of the narcotic drugs in the country.

Customer''s Clustering is an instrument for considering the needs which were not allowed to be expressed due to mass marketing. The primary goal of market segmentation is to find and retain those customers we want to serve. In this paper، we present the experimental results of clustering bank''s customers using artificial neural networks (ANN) compared with traditional statistical methods. To cluster the customers، 7 key distinctive characteristics of 600 customers of a bank were extracted. Customers’ clustering was performed using ANN and a powerful statistical Ward Method. The results were compared using discriminant analysis، MAPE and RMSE. The comparisions indicate the superiority of ANN output over WARD. Clustering by ANN indicates the strength and innovation of this study. Furthermore، focusing on importance of solving the death neuron problem in artificial neural networks by BIAS term is a contribution of this paper.

Production firms select and design their proper production system by attention market and resources. Production systems or production process be introduced by series of variables. The one of their most famous is product-process matrix of Hayes and wheelwright. It intoduce production process by using product adult and process adult variables. In this research، after survey previous studies، be recognized new dimentions to intoduce production systems. These dimentions defind by structural and infra-structral manufacturing decisions. A Sample with size 245 be selected from production firms in iran. Multiple discriminant analysis used to analys data. Results show that could introduce Iranian production systems on “Technology-Source” and “Quality plans” dimentions. Finnaly، represent conclutions and recommends for future researches.