• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.

• The Journal of Information Systems
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• v.21 no.3
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• pp.137-161
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• 2012

The increasing interest in big data analysis using various data mining techniques indicates that many commercial data mining tools now need to be equipped with fundamental text analysis modules. The most essential prerequisite for accurate analysis of text documents is an understanding of the exact semantics of each term in a document. The main difficulties in understanding the exact semantics of terms are mainly attributable to homonym and synonym problems, which is a traditional problem in the natural language processing field. Some major text mining tools provide a thesaurus to solve these problems, but a thesaurus cannot be used to resolve complex synonym problems. Furthermore, the use of a thesaurus is irrelevant to the issue of homonym problems and hence cannot solve them. In this paper, we propose a semantic text mining methodology that uses ontologies to improve the quality of text mining results by resolving the semantic ambiguity caused by homonym and synonym problems. We evaluate the practical applicability of the proposed methodology by performing a classification analysis to predict customer churn using real transactional data and Q&A articles from the "S" online shopping mall in Korea. The experiments revealed that the prediction model produced by our proposed semantic text mining method outperformed the model produced by traditional text mining in terms of prediction accuracy such as the response, captured response, and lift.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.223-235
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• 2022

The satisfaction and performance levels of employees also depend upon the leadership styles adopted by corporate leaders. Meanwhile, organizational identification is a fundamental organizational behavioural concept in business that influences employee belongingness with the organization. Taking into account the relevance of this research topic, this paper aims to understand of organizational identification and leadership styles in SMEs. It also investigated the mediation role of organizational true. For the analysis, a questionnaire survey was conducted on employees of SMEs, and the collected data were analyzed using the hierarchical multiple regression analysis. Analysis results are as follows: First, out of leadership style, transformational leadership, transactional Leadership had a positive effect on job satisfaction. Second, organizational identification had a positive effect on job satisfaction. Third, in the relationship between leadership, organizational identification and job satisfaction, the mediating effect of organizational true had significant transformational leadership→organizational truer→job satisfaction, transactional leadership→organizational truer→job satisfaction, organizational identification→organizational truer→job satisfaction. The results of this study show that the role of middle managers is very important in SMEs. The leadership of SME managers can also be linked to organizational performance through the job satisfaction of workers. Therefore, SME' CEO should provide opportunities to receive professional training on the leadership of middle managers. In addition, SME' CEO need a strategy to instill a positive image of the organization in workers through the organizational vision.

• IE interfaces
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• v.21 no.3
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• pp.343-353
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• 2008

Vendor-managed inventory(VMI) is a supply chain strategy to improve the inventory turnover and customer service in supply chain management. Unfortunately, many VMI programs fail because they simply transfer the transactional aspects of placing replenishment orders from customer to vendor. In fact, such VMI programs often degrade supply chain performance because vendors lack capability to plan the VMI operations effectively in an integrated way under the dynamic, complex, and stochastic VMI supply chain environment. This paper presents a decision support system, termed DSSV, for VMI in the retail supply chain. DSSV supports the market forecasting, vendor's production planning, retailer's inventory replenishment planning, vehicle routing, determination of the system operating parameter values, retailer's purchase price decision, and what-if analysis. The potential benefits of DSSV include the provision of guidance, solution, and simulation environment for enterprises to reduce risks for their VMI supply chain operations.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.127-136
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• 2017

The strategy that using data collection from Netflix uses for its services is different from traditional human interaction and the communication, and it is represented by the systematic algorithm that rooted from intelligent information system based on the human interaction and communication. These characteristics allowed the study to reflect the influence of 'Asset specificity' which affects the continuous consumption of the media services of Netflix users through economic psychological analysis based on transactional cost economics. The result from the survey on actual Netflix users, three types of specificity (Space specificity, time specificity, relational specificity) reduced perceived searching cost whereas perceived instrumentality has increased, eventually reinforces the commitment to the service. This implies that the service characteristics of Netflix, trying to communicate with the individuals based on intelligent information system are distinct from the existing platform services and it gives the significance of work very effective for user's continuous consumption of the media services.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.1
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• pp.105-124
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• 2000

The purpose of this paper is to investigate the relationships among transformatonal leadership, gropefficacy, and group performance. A total of 321 empolyees of a fire and marine insurance frim in Seoul anonymously completed the Multifactor Leadership Questionnaire-Form V, which consists of three factors(charisma, individualized consideration and intellectual stimulation) for transformational leadership, and two factors(contingent reward and management by exception) for transactional leadership. The sample, which largely consists of sales supervisors and salesmen, includes 41 sales office branches. The findings of the study are as follows. Transformational leadership is closely associated with group-efficacy and group performance. That is, there are significant correlations between transformational factors and group-efficacy, between the factors and group performance, and between group-efficacy and group performance. A stepwise multiple regressio analysis revealed that transformational leadership augmented the subordinates's extra efforts. It was also found that group-efficacy was mediating the relationship between transformational leadership and group performance. The managerial implications of these findings and future directions of research are also discussed.

• Journal of Korean Academy of Nursing Administration
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• v.12 no.2
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• pp.196-203
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• 2006

Purpose: The Purpose of this study was to identify the relationship between leadership styles and empowerment of nursing students. Method: The subjects were 386 nursing students who were in college and university. The data were collected from July 26 to September 18, 2004 by the structured questionnaires. For data analysis, descriptive statistics, Pearson correlation coefficient, t-tets and ANOVA with SAS package were used. Results: Transformational leadership showed a significant difference according to school career, present grade, interpersonal relations, admission motive, satisfaction degree for nursing, satisfaction degree for practice, meaning on nursing job and transactional leadership showed a significant difference according to last session study score, satisfaction degree for nursing. Empowerment showed a significant difference according to school career, present grade, interpersonal relations, satisfaction degree for nursing, satisfaction degree for practice, meaning on nursing job. Charisma, intellectual stimulation, individual consideration and contingent reward perceived by nursing students were positively related to empowerment. Management by exception perceived by nursing students was negatively related to empowerment. Conclusion: The result of this study may be helpful in empowerment improvement of nursing students.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5287-5303
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• 2018

Handling vast amount of data found in large transactional datasets is an obvious challenge for the conventional data mining algorithms. Addressing this challenge, our paper proposes a parallel approach for proper decomposition of mining problem into sub-problems in order to find frequent patterns from these datasets. The proposed, Pattern Mining for Large Distributed Dataset (PMLDD) approach, ensures minimum dependencies as well as minimum communications among sub-problems. It establishes a linear aggregation of the intermediate results so that it can be adapted to large-scale programming models like MapReduce. In this context, an algorithmic structure for MapReduce programming model is presented. PMLDD guarantees an efficient load balancing among the sub-problems by a specific selection criterion. Further, it optimizes the number of required iterations over the dataset for mining frequent patterns as compared to the existing approaches. Finally, we believe that our approach is scalable enough to handle larger datasets in terms of performance evaluation, and the result analysis justifies all these mentioned concerns.

• Journal of the Korean Society of Safety
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• v.35 no.6
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• pp.61-77
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• 2020

In order to establish a conceptual basis and future research direction of safety leadership, this study reviewed domestic and foreign research trends related to safety leadership through systematic literature review methods. The literature search was conducted by combining terms related to safety leadership without limiting the period databases. A total of 195 documents were found, of which the final 59 were used for analysis. As a results, the safety leadership study was the most frequent in relations among variables. The most leadership types were based on transactional leadership and transformational leadership. In addition, studies have been conducted to categorize safety leadership as an independent concept. Safety leadership was mainly studied in the fields of safety engineering, disaster prevention, and business administration. Quantitative studies were mainly conducted to research methods. Based on the results, the research trend related to safety leadership was discussed, and suggestions for future research direction was presented.

• Iberoamérica
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• v.22 no.1
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• pp.111-148
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• 2020

One way for phatic communication to be linguistically realized involves ritual activities, such as greetings and leave-takings. These conventionalized acts in medical contexts can significantly influence both transactional and interpersonal goals. The analysis in this paper confirms that exchanging rituals such as greeting and leave-taking between doctors and patients is not a simple exchange of conventionalized linguistic symbols. In addition, the use of discursive strategies means that to determine whether an expression is phatic or not, it is necessary to analyze it from the multidimensional perspective. The phaticity is established based on the negotiation between the participants during the interaction. We have found that the interrogative form of greeting like "¿Qué tal?" (How are you?) becomes a versatile resource in the medical context. Thus, professionals need to be attentive to the discourse progress, because the phaticity of the interrogative greetings (illocutionary force) is linked, in the vast majority, with the reaction of the patients. Also, the data confirms that when participants coordinate closings, the exchange of turns lengthens and the intervention of various discursive strategies for phatic communion becomes more prominent.