• Title/Summary/Keyword: Customer Learning Process

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A Case Study on the Establishment of a Strategy System through the BSC of SMEs (중소기업의 BSC를 통한 전략체계 구축 사례연구)

  • Lim HeonWook;Kim WooSu
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.303-308
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    • 2023
  • The purpose of this study is to provide a practical guide for establishing BSC that can be practically applied by SMEs. To this end, a case study was conducted to establish a performance evaluation system through a field-required Balanced Scorecard (BSC) for company J, a tent pole manufacturer, and to provide a management strategy system map. As a survey method, the requirements of the ordering organization were organized through a comparison of the BSC-related proposal requests in the first stage. The BSC establishment method was organized through the arrangement of the second stage result report. The 3rd stage BSC derived KPI indicators for SMEs for each of the 4 perspectives. A corporate vision was derived through a 4-step SWOT analysis. A strategy map was developed through 5-step field-required KPI, weight setting, and BSC. The 6-step final strategy system was also drawn up. As a result of the study, the four perspectives of the BSC were reconstructed by department. That is, the financial (financial) perspective is from the executives' perspective, the customer's perspective is from the sales department's perspective, the internal process perspective is from the design department/production quality department's perspective, and the learning/innovation perspective is from the management department's perspective. In addition, a total of 11 CSFs and a total of 49 KPIs of J company were derived. The limitation of the study is that the final strategy system through the company's BSC has only been carried out, and it needs to be linked with the company's compensation system in the future.

A Hybrid SVM Classifier for Imbalanced Data Sets (불균형 데이터 집합의 분류를 위한 하이브리드 SVM 모델)

  • Lee, Jae Sik;Kwon, Jong Gu
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.125-140
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    • 2013
  • We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

The Needs of Students and Practitioners on the Education Curriculum of Innovative Product Development (혁신제품개발 교육과정에 대한 학생과 산업체 실무자의 요구사항 분석)

  • Lee, Won-Sup;Jung, Ki-Hyo;Chang, Joon-Ho;Chang, Jun-Ho;You, Hee-Cheon;Chang, Soo-Y.;Jun, Chih-Yuck;Jung, Moo-Young;Han, Sung-H.
    • Journal of Engineering Education Research
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    • v.11 no.4
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    • pp.11-18
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    • 2008
  • Companies have been making considerable efforts to develop innovative products for better competitiveness in the market, however, the education curriculum for innovative product development (IPD) in domestic universities needs has not been well developed. The present study was intended to identify the needs of students and practitioners regarding teaching subjects, pedagogical methods, and industry-academia collaboration that can be reflected in the development of IPD education curriculum. Through a literature survey 46 IPD teaching subjects of 7 categories (planning, feasibility analysis, concept development, product design, manufacturing process design, production, and ethics & law) were selected. Opinions on the preferences and importances of the teaching subjects, pedagogical methods, and industry-academia collaboration were collected from 53 college students who took courses of product development and 36 practitioners working in product development. While the students preferred the balanced teaching of all the subject categories, the practitioners suggested planning and concept development be taught with high importance; 6 subjects (product development strategy, customer needs identification, market research, concept generation method, design ideation method, and ergonomic design) received high ratings of preference and importance. The students preferred the mix of various pedagogical methods (lecture, discussion, presentation, practice, and case study) and provided needs on each pedagogical method. Lastly, the students wanted an opportunity of learning through industry-academia collaboration and the practitioners provided ideas for mutual benefits between industry and academia. The needs of students and practitioners identified in the study can be effectively applied to develop a better IPD education curriculum.

A Study on the Effectiveness of 3PL Logistics Information System : A Focus on the Role of Supply Chain Performance in Shipper and Long-term Relationship intention (3PL 물류정보시스템의 효과성에 관한 실증적 연구 : 화주기업의 공급사슬성과와 장기지향적관계성의 역할을 중심으로)

  • Cho, Jae-yong
    • Journal of Venture Innovation
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    • v.3 no.2
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    • pp.111-128
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    • 2020
  • Recently, in the process of globalization of companies, the use of third party logistics providers (3PL) has been strengthened. Therefore, the purpose of this study is to test the effectiveness of the logistics information system provided by 3PL companies. This study is to test the relationship between the effect of the characteristics of the 3PL logistics information system on the shipper's supply chain performance, that is, logistics performance, customer performance, and organizational performance, and the shipper's loyalty to the 3PL company, that is, 3PL corporate performance. In addition, long-term relationship orientation is to test whether there is a moderating effect between the shipper company and the 3PL company. Through this, this study aims to provide strategic implications for improving the competitiveness of 3PL companies. In this study, a total 205 data were collected and used for analysis of shippers companies for hypothesis testing, and analyzed using SPSS 21.0 and AMOS 21.0 statistical programs. The results of the study are summarized as follows. First, it was found that the accuracy, timeliness, and usefulness of the 3PL logistics information system all had a significant positive (+) effect on the performance of the shipper's supply chain. Second, it was found that the accuracy, timeliness, and usefulness of the 3PL logistics information system all had a significant positive (+) effect on 3PL corporate performance. Third, it was found that the performance of the supply chain of the shipper company had a significant positive (+) effect on the performance of the 3PL company. Finally, it was found that long-term relationship orientation had a moderating effect on the relationship between the performance of the shipper company's supply chain and the performance of the 3PL company. The purpose of this study is to provide academic and practical implications for securing competitive advantage through the logistics information system of 3PL logistics companies.