• Journal of Distribution Science
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• v.15 no.12
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• pp.95-102
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• 2017

Purpose - This study aims to develop diagnostic indices for managerial performance of agro-food distribution corporations. In particular, weights of diagnostic indices were estimated using the AHP method. Management diagnosis on agro-food distribution corporations is expected to increase their competitiveness in the domestic market as well as in international markets. Research design, data, and methodology - It develops weights or importance of the diagnostic indices based upon the survey of 21 experts in food distribution management. The survey was carried out using e-mail. Management diagnostic indices were developed based upon four BSC(Balanced Scorecard) perspectives of finance, learning/growth/leadership, customer, and internal process/technology. Results - Diagnostic indices on financial perspective consist on profitability, productivity, growth, stability and activity. Learning and leadership perspective indices consist of management will, CEO leadership, level of learning, innovation, and level of management information system. Customer perspective indices are branding, customer and channel management and internal process/technology indices consist of fourteen sub-indices representing technologies, efficiency, and dynamics. It was estimated that the weight of financial perspective index was 0.3, internal process/technology perspective index 0.248, customer category index 0.247, and learning, growth and leadership perspective index 0.205. This study also estimates weights of sub-indices for managerial diagnosis by four different perspectives. Estimated weight of profitability (0.085) is the greatest among financial perspective indices, followed by stability (0.072), growth (0.053), productivity (0.051), and activity (0.038). While estimated weights of leadership, capability, and information indices are 0.100, 0.061, and 0.044 respectively, weights of marketing, customer management, and quality and service indices are 0.104, 0.093, and 0.051, respectively. Among internal process/technology perspective, estimated weights of efficiency, technology, and innovation indices are 0.106, 0.088, and 0.054, respectively. Conclusions - The diagnostic indices for managerial performance of agro-food distribution corporations would be utilized by agro-food distribution corporations themselves, extension service institutions, and consultants. It is also expected that central and local governments use diagnostic indices developed in this study for the purpose of evaluating the effects of governmental support programs for agro-food distribution corporations. Futhermore researchers and consultants would modify diagnostic indices developed in this study, reflecting characteristics and situation of types of agro-food distribution corporations.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.325-333
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• 2019

This study was conducted to investigate the factors affecting satisfaction and dissatisfaction of e-learning learner students using Kano model and Timko's customer satisfaction coefficient. The results of the analysis showed that firstly, the students are highly satisfied when it is convenient to learn visually and audibly, when the students can ask questions at any time, and when the professor was interested in the students. Second, the rational criteria and accurate evaluation of grades and assignments were confirmed as factors that should be satisfied. Third, unlike the results of the basic study that the students use e-learning due to the convenience of learning time and learning space and the ease of learning process, it is no longer an attractive factor to use e-learning. The results of this study suggest that it is possible to present effective directions for the development of e-learning education and strategic application of each factor classified by the two-dimensional recognition method.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.165-177
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• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• International Commerce and Information Review
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• v.11 no.1
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• pp.239-264
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• 2009

As the competitive market environment and industry circumstances become more and more competitive on a daily basis, it is not easy to find an opportunity to initiate small business, or increase performances of Small and Medium Business. The research findings are as follows. First, entrepreneurship(innovation, progressive, social responsibility) has significant effects on the market orientation. Second, company competence(individual resource, technology resource) has significant effects on the market orientation. Third, market orientation has significant effects on the non-financial performance(Internal process performance, learning & growth performance, customer performance). Finally, non-financial performance(Internal process performance, learning & growth performance, customer performance) has significant effects on the financial performance.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• IE interfaces
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• v.25 no.2
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• pp.178-186
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• 2012

The DRAM module is an important part of servers, workstations and personal computer. Its malfunction causes a lot of damage on customer system. Therefore, customers demand the highest quality products. The company applies DRAM module Outgoing Quality Assurance Inspection(OQA) to secures the highest quality. It is the key process to decides shipment of products through sample inspection method with customer oriented tests. High fraction of defectives entering to OQA causes inevitable high quality cost. This article proposes the application of ensemble learning to classify the lot status to minimize the ratio of wrong decision in OQA, observing a potential in reducing the wrong decision.

• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.153-168
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• 2018

Purpose: The balanced scorecard (BSC) has been adopted to evaluate factors affecting performances in organizational dealer marketing in Chinese cosmetics market. Four performance measures in BSC: learning & growth, internal business processes, customer performance, and financial performance are employed in our empirical study. Methods: We conducted surveys of dealers in a Chinese cosmetics company and used total 463 samples for analysis. Confirmatory factor analysis and structural equation model analysis were employed using AMOS 20.0. Results: This study found that internal business process had a positive relation with customer performance and learning and growth. Also, customer performance and learning & growth positively affected financial performances. Conclusion: This study has some academic and practical contributions in that the revised BSC model reflects the special aspects of Chinese cosmetics market and it can be used as a guide for companies in the Chinese cosmetics market to understand which factors are affecting performances.

• Journal of Information Technology Applications and Management
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• v.20 no.3
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• pp.143-167
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• 2013

The main propose of this research is to examine the performances in ERP introduced enterprises by utilizing BSC model proposed by Kaplan and Norton [1992], to realize this goals, a theoretical review on ERP, BSC, and other related issues is performed in advance, accordingly, research model was generated. In conceptual model analysis, we focused on casual relationships among four performance measurement indicators after introduction of ERP proposed by Kaplan and Norton [2000]. To test the model, structural equation modeling is employed to analyze data collected from 164 enterprises which have introduced ERP for more than 1 year. Survey respondents were confined within the representatives of each enterprise's ERP. Hypotheses proposed in our research are tested by covariance structure model, results are listed as follow : First, learning and growth performance is significant factors for improving both internal process performance and customer performance; second, process performance has a positive impact on customer performance third, despite that customer performance is positively related to financial performance, no direct relationship is found between internal process performance and financial performance, an indirect relationship is built through intermediate medium of customer performance. Based upon these results, we discuss implications at the latter part of paper. Meanwhile, we also provide research limitations, and future research in the final section.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.339-349
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• 2020

The study evaluates the performance of public hospitals in Vietnam by applying the Balanced Scorecard (BSC). The authors first review the literature to find the research gap of performance in public hospitals. Then, we built Likert questionnaires to collect data from more than 200 managers of public hospitals in the Northwestern provinces of Vietnam. The research uses correlation regression to evaluate the performance based on the influence of factors in the BSC model, including Strategic planning, Internal process, Finance, Mission, Customer, and Employee learning and growth. The results show that the performance of public hospitals in the research sample is influenced by the factors in the BSC model in descending order based on the regression coefficient as follows: Internal process, Finance, Mission, Strategic planning, Customer, Employee learning and growth. Based on the quantitative research findings, we continue by conducting some deep interviews with specialty to propose intensive recommendations about how to implement Mission, Internal process, Financial policies, etc. to managers in public hospitals with an aim to improve the performance of public hospitals in the Northwestern mountainous region of Vietnam. The lessons could be applied for other public hospitals in Vietnam and other jurisdictions that have similar conditions.

• International Journal of Quality Innovation
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• v.9 no.2
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• pp.11-30
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• 2008

The purpose of this study is to develop BSC model of social enterprise. Performance analysis tool of BSC have been brought over from the business world, designed and created from the perspectives of profit-based businesses. The BSC is a strategic performance measurement and management tool designed for the private sector acting as a communication/information and learning system, to measure 'where we are now' and 'where to aim for next'. It prescribes a plan for translating 'vision' and 'strategy' into concrete action across four perspectives at different stages, depending on the business. These perspectives are 'financial', 'customer', 'internal processes' and 'learning and growth', each of which is connected by cause-and-effect relationships that reflect the firm's strategy. Social aims of social enterprise are to accomplish desired outcomes which are to employ vulnerable people and to provide social services. The measurement factors of financial perspective are stable funding, efficiency of budgeting, stakeholders' financial supports, and trade profit. The measurement factors of customer perspective are government, social service users, employees, local communities, sup plier, social activity company, and partnership with external organizations. The measurement factors of internal process perspective are organizational culture, organizational structure/management, internal/external communication, quality of products and services, information sharing. The measurement factors of learning and growth perspective are training and development, management participation, knowledge sharing, leadership of CEO and manager, and learning culture.