• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.99-120
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• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

• Journal of Environmental Health Sciences
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• v.36 no.5
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• pp.391-401
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• 2010

A reduction in risk of occupational exposure to chemical hazards within the workplace has been the focus of attention both through industry initiatives and legislation. The aims of this study were to develop an exposure matrix by industry and process, and to apply this matrix to control the risk of occupational exposure to Dichloromethane (DCM). The exposure matrix is a tool to convert information on industry and process into information on occupational risk. The exposure matrix comprised industries and processes involving DCM, based on an exposure database provided by KOSHA (the Korean Occupational Safety and Health Agency), which was gathered from a workplace hazards evaluation program in Korea. The risk assessment of the exposure matrix was performed using Hallmark risk assessment tool. The results of the risk assessment were indicated by a Danger Value (DV) calculated from the combination of hazard rating (HR), duration of use rating (DUR), and risk probability rating (RPR) of exposure to the chemical, and were divided into four control bands which were related to control measures. The applicability of the risk assessment of the exposure matrix was evaluated by a field study, and survey of the employees of the exposure matrix groups. Among 45 industries examined, this study found that greater attention should be paid to two industries: the manufacture of other optical instruments and photographic equipment, and the manufacture of printing ink, and to one process among 47 examined, the packing process in the manufacture of printing ink, because these were regarded as carrying the highest risk. This tool of a risk assessment for the exposure matrix can be applied as a general exposure information system for hazard control, risk quantification, setting the occupational exposure limit, and hazard surveillance. The exposure matrix includes workforce data, and it provides information on the numbers of exposed workers in Korea by agent, occupation, and level of exposure and risk.

• Journal of Distribution Science
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• v.13 no.1
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• pp.27-33
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• 2015

Purpose - The ICT market in the EU is lagging behind that of the US; however, algorithm and software development within the EU have grown steadily, and they involve focusing on the creative cultural convergence conceptualized as part of Horizon 2020 and connecting neighboring markets in the EE and the Mediterranean region. It is essential to study the requirements to market the EU's creative ICT development in emerging industrial countries after examining its applicability in these countries. Research design, data, and methodology - This study deals with data pertaining to the EU's creative industry and competitive edge. The global cultural expansion of the EU facilitates a new concept involving not only low-cost IT products to enhance local cultural artifacts through R&D and the construction of efficient infrastructure services, but also information exchange with a realistic commercialization of the technology that can be applied for creative cultural localization. In the European industry, research on algorithms has been applied for the benefit of consumers. We investigated how the process is conducted in the EU. Results - Europe needs to adjust its economic structure to the local culture as part of IT distribution convergence. The convergence has been converted into a production algorithm with IT in the form of low-cost production. This is because there is an attempt to improve the quality of transport infrastructure, workforce availability, and the distribution of the distance to the local industries and consumers, using IT algorithms. Integrated into the manufacturing industry, based on the ICT infrastructure and solutions, smart localized regional clusters are formed with the help of grafting. Europe has own strategy to increase the number of hub-and-spoke cities. Europe is now becoming integrated, with an EPC system for regional cooperation rather than national competition in ICT technology. Europe has also been recognized in this study as changing the step-by-step paradigm for global competitiveness through new creative culture industries. Conclusions - As a result, there are several ways of converging with others through EU R&D intensity; therefore, the EU can be seen as successfully increasing marginal value, which is useful in developing a special industrial cluster or local cultural cities that create converged development by connecting people and objects with IT. In fact, when compared to the US, Europe has a strong culture and the car industries have a tendency to overshadow the IT industries with integration of services in IT distribution. Considering the rapid environmental changes, the convergence of IT services is likely to take place in Europe, similar to the pharmaceutical industry and the automotive industry. This requires a focus on human resources and automated systems management. The trend is to move away from low-wage industries, switched to key personnel centers of the local university-industry. EU emphasizes the creation of IT market demand in Europe involving local cultural convergence for marketing as the second step to strengthen the economic hub-and-spoke areas.

• International Area Studies Review
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• v.21 no.4
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• pp.195-222
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• 2017

This exploratory study analyses the factors, sources and effects of the regional competitive advantage of Jeju Island in Korea in global competition era. The competitive advantage of Jeju Province is analysed with the triple diamond model based on Porter's model for the competitive advantage of nations. The competitive advantage factors of Jeju Province are measured through the competitive advantage of the hospitality industry, which is one of the major industries of Jeju Island. These factors include outstanding natural landscape, domestic hospitality industry workforce, social overhead capital, massive domestic and international tourists, growth of related industries such as duty free shops and casinos, and coincidences such as Jeju Olle trail construction and Chinese government's international travel approval. Since these factors are based on local, domestic and international management resources, this study suggests that obtaining such resources is critical among Jeju hospitality industry in gaining the competitive advantage. Although the competitive advantage of Jeju hospitality industry is increasing, the organic connections with the regional economy are required for improvements on Jeju residents' quality of life. This study examines the factors and origins of competitive advantages on a regional level instead of a national level, and further investigates how the characters and origins of these factors affect the local economy. The results suggest that the triple diamond model is suitable for evaluating the regional competitive advantages.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.113-129
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• 2015

Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place's location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt's evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper's methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability. The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.