• International Journal of Quality Innovation
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• v.3 no.2
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• pp.159-173
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• 2002

Any organization's Six Sigma program may be at high risk without heeding the lessons learned from the past and that tries to operate without a robust business foundation. A foundation that preferably should consist of stepping-stones such as a 5-S house-keeping program, an effective Integrated Management System (IMS), which includes a strong focus on planning for quality to fully capture the Voice of the Customer (VOC), and an organization-wide training scheme, as well as a reliable Cost of Poor Quality (COPQ) system. That's the best advise I can give to any organization that wishes to embark on a Six Sigma improvement program and hope to be successful. The paper will elaborate on the above issues and provide suggested solutions based on the review of published historical information and the experiences encountered over the last four decades by the author, as a quality practitioner and consultant, in industries that produced safety-critical product. This author maintains that few fundamentally new or useful things have been created in the field of Quality during the last couple of decades. Nevertheless, this paper deliberates on a number of relatively “newer” issues including the concept of “three types of customers”, the CTC, “Critical To Customer” term, the eight Quality Management Principles of the new ISO 9000 family, the growth of industry-specific standards, the adoption of Integrated Management Systems, the rebirth of AS2561 COQ standard, the spread of Six Sigma as well as related ASQ certification and the need for a robust business foundation to ensure Six Sigma survival.

• Journal of East Asia Management
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• v.2 no.1
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• pp.105-132
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• 2021

The purpose of this study is to summarize recent research on new product development (NPD) and to examine the direction of future research on NPD. In recent years, product development has also become more diversified due to the formation and disappearance of new markets, the increasing commoditization of products, and the emergence of new technological infrastructures such as ICT and crowdsourcing. In addition, NPD research is also in a situation where new research is emerging along with the progress of research in related areas, such as open innovation and customer participation. On the other hand, research on NPD has become increasingly fragmented into themes related to NPD as research progresses, making it more difficult to grasp the overall picture of NPD research, although review articles on NPD have been written. Not many review articles have been written in a way that goes beyond the individual themes of NPD research. However, even though it is impossible to look at NPD research as a whole, this study believe that by daring to conduct an exhaustive review of recent NPD research, rather than individual issues, and by understanding the types of discussions that have taken place in recent NPD research, this study can identify areas that require further discussion. Based on the above, the purpose of this study is to comprehensively examine and organize the topics and issues that have been dealt with in recent NPD research, point out the topics that have not been adequately dealt with in previous research, and indicate the direction of future research. This study found that (1) half of the previous studies this study reviewed dealt with the topic of collaboration in NPD, (2) existing studies on NPD assume that the purpose of NPD is to gain competitive advantage through differentiation, but the formation of the market itself through NPD has not been discussed However, it became clear that there has been no discussion of the formation of the market itself through NPD. While the formation and disappearance of new markets has become a common phenomenon in recent years as the competitive environment changes more and more rapidly, the formation of new markets through NPD may also be discussed as a new research area of NPD. However, the formation of new markets through NPD could be discussed as a new research area of NPD. This study examined the possibility of discussing the formation of new markets through NPD by using market category studies.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Management & Information Systems Review
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• v.36 no.5
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• pp.45-60
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• 2017

This study aims to elucidate the key improvements through the current state of customer support for smart home services based on the Internet of things and the evaluation of user's usage. Smart home services typically provide a wide range of value in terms of security, safety, manageability (electricity and water use), convenience, and remote management accessibility. In this study, we analyzed the current state of smart home service based on Internet of Samsung, SKT and LG U + companies in Korea. However, since LG U+ is the only company providing user reviews, there is a limit to generalization, but we are trying to figure out whether the customer value is conveyed properly or not, and in which part the customer support is focused to support the service. As a result of analyzing the results of the study, we found that the smart home service is commercialized and marketed in various forms. However, it is questionable whether the technological level and user satisfaction level are sufficiently satisfied. The results of this study are as follows. First, although each company provides usage guidance, they still ask many questions about joining products and using products. Second, there are many defects in the product itself, and it is found that the companies are not satisfied with the overall response. Third, the three companies are focusing on switches, outlets, sensors, and lamps. This is an individual intelligent product rather than an interlocking or linking level, and it can be seen that there are many parts that are not compatible with the concept of the original Internet of things. In conclusion, this study shows that there are still many areas to improve on the level of customer service provision of smart home service, in particular, the ease of use is low and the quality of products is not reliable. We would like to present the improvement of this in detail through this study and reflect the companies that provide it and the service providers.

• Information Systems Review
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• v.13 no.1
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• pp.75-96
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• 2011

This research uses coolhunting to predict the future trend of e-Commerce industry. Coolhunting is a method to take Cool Trends which are the future trend through social network analysis for discovering the trendsetter and its collective intelligence. Coolhunting is generally carried out by social network analysis while this research uses NodeXL of social network analysis tools. We designed industrial network research model for relation among e-Commerce corporation, product, the types of customer service and customer service employee to discover the Cool Trends of e-Commerce industry. According to the result of this research, e-Commerce industrial network was being changed from chaos to collective intelligence form. As a analysis result for network influences, we found that Cool Trends of e-Commerce industry invigorate social commerce industry through the collective intelligence focusing intelligence VIP, Excellence, grade of Administrating for women customers(trendsetter) and it promotes semantic consumption from customers and purchasing power will be concentrated on cosmetic, beauty, perfume product categories in social commerce. We propose the strategic direction for e-Commerce corporation and hope that domestic e-Commerce corporation continues to grow and high-quality services are provided for customers.

• Korean Business Review
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• v.17
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• pp.83-110
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• 2004

In modern society, there exists a growing tendency that the product image, rather than the substance of the product, is given more and more emphasis. In other words, consumers tend to purchase a product whose brand image coincides with their self image. Today, it is one of the essential factors for marketing strategy of a modern enterprise to have brand image perceived by consumer self-image. The image, by affecting the perception of consumers, explains the reason why some consumers choose one brand out of many brands that are available to them. Furthermore, brand-image perceived by consumers becomes more important factor in improving the company's market share. For this research, we investigated the theoretical background based on previous studies and collected statistical data through a market survey. The results of the actual research indicate that the attributes of the images differ notably depending upon demographic attributes; that the brand image judged by a customer is positively correlated to the customer's self image; and that the regression analysis of the purchase intention in accordance with coincidence of independent variables proved to be insignificant. But the correlation analysis of the variables shows that the sensuous image of a perceived brand image product notable differences in the purchase intention. Most of Consumers tend to prefer certain brand of causal wears in accordance with their cognized brand-image and self-image: social self-image and actual self-image. Corporate must not spare any effort to establish differential advantage. through better image or changing image. Also marketers have to identify the strengths and weakness of their brand in relation to the competition in setting up their brand management strategy. In conclusion, the outcomes of the study suggest that the consumers purchase the images of the brands, rather than the products themselves. Accordingly, in the clothes markets with similar quality levels, the emphasis should be put on differentiation of the brand images in order to further increase sales and maximize profits.

• Culinary science and hospitality research
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• v.10 no.3
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• pp.97-118
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• 2004

As the economy grows rapidly and the national income level increases, the service industry has become more important and its size gets larger. Especially, the food industry undertakes a continuing growth of consumer expenditures through no nationalization of food, consumers varying patterns of eating out, and individualization. However, it includes many problems with improving service quality towards customers owing to the absence of systems and philosophy to realize customer satisfaction management Therefore, this study conducted a study with Korean traditional restaurant customers to measure their perceived service quality, to verify what factors most influence consumer satisfaction, and to suggest ways to meet the costumer needs by integrating the study results and developing high service quality. To sum up the results of this study, Korean traditional restaurant visitors evaluated three dimensions of service quality overall favorably. Interestingly, background music received a lower level of satisfaction. This implies that the Korean traditional restaurant managers do not do a fine performance in managing music as an ambient element to evoke the atmosphere of the restaurant. Customers showed a lower satisfaction with menu price among the factors measuring product quality. As a result of this study, several suggestions have been made as follows: First, it is necessary for the Korean traditional restaurants to provide systematic employee training to instigate a service culture of customer focus. Secondly, it is important to develop traditional foods using ingredients produced in the region based on a literature review of food in Gyeongju, Silla. Thirdly, it is an urgent task to develop regional menus to revitalize the restaurant business. Fourthly, it is important to provide safety food through systematic sanitary administration. Lastly, it is necessary to limit the number of menu items and attempt specialization of them. Such an attempt with specialized menu items will help their food taste and quality improve and thereby reduce inventory burdens. However, this study has a few limitations. Since this study conducted a survey of the restaurants which provides only Korean traditional food in Gyeongju, not all the restaurants in it, there is a limitation in measuring customer satisfaction with service quality. Therefore, the study results cannot be generalized to all the restaurants in Gyeongju and the nation. Finally, this study suggests that studies on the relationships between customer satisfaction and menu price and customer value system or further customer satisfaction studies with Korean traditional restaurants should be continued.

• Management & Information Systems Review
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• v.2
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• pp.209-235
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• 1998

Traditional cost system is distorted due to the using unit-based measure. It is being criticized that it do a poor job of attributing the expenses of support resources to the production and sales of individual product. Activity Based Cost System expend the range of second-stage cost assignment drivers beyond the traditional measures of labor and machine times, units produced, and material quantities to allow for drivers that measure the amount of batch-level, product-sustaining, and facility-sustaining activities performed. It is a resources consumption model of organization, not just a more complex cost accounting of cost allocation system. This paper proposes a enterprise resource planning by activity based management. To effective performance system for company that want to be setting competitive levels, the information systems must support a fast moving, rapidly changing. Activity based management is a process of accumulating and tracing cost and performance da to a firm's activities and providing feedback of actual results against the planned cost to initiate corrective action where required. Therefore this system provides a highly powerful decision-making tool. To construct this system, we need Enterprise Resource Planning System. Since ERP is designed around the idea that rapid change and a degree of unhandled change is normal, it allows driving the customer's rapidly needs much deeper through the business cycle.

• Management & Information Systems Review
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• v.13
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• pp.71-97
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• 2003

As an electronic commerce grows in a rapid speed today, it has a great effect on not only our consuming lives but also the marketing activities. The study on involvement levels and consumer satisfaction in physical market in the existing studying papers in home was made progress rapidly. But, the study on involvement levels and consumer satisfaction in virtual market leaves much to be desired. This paper aims at considering the relationship between the involvement levels and the consumer satisfaction factors in the electronic commerce through the internet shopping mall whose importance is emphasized day by day. In this paper, three following questions were studied: (1) what is the difference among the factors(product/service/image) of consumer's satisfaction in accordance with consumers' involvement levels, (2) what is the difference in an intention of repurchase in accordance with the consumers' satisfaction factors, and (3) what is the difference in an intention of repurchase in accordance with the involvement levels and the consumers' satisfaction factors. As a result of analysis, only the service one of the factors of consumer's satisfaction has a difference in accordance with high/low involvement, and also, the factors which have an effect on the intention of repurchase were product, service and image.