• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Journal of Food Hygiene and Safety
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• v.36 no.1
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• pp.42-50
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• 2021

Along with the rapid growth of the food service industry, food safety requirements and hygiene are increasing in importance in restaurants and hotels. Accordingly, there is a need for quick and practical monitoring techniques to determine hygiene status in the field. In this study, we investigated 5 domestic 5-star hotels specifically, personal hygiene (hands of workers), cooking utensils (knife, cutting board, food storage container, slicing machine blade, ice-maker scoop) and other facilities (refrigerator handle, sink). In addition, we examined the hygiene management status of customer contact points (tongs for buffet, etc.) to derive the correlation between the ATP values as a, a verification method. As a result of our five-hotel survey, we found that cooking utensils and personal hygiene were relatively sanitary compared to other inspection items (cookware 92.2%, personal hygiene 91.4%, facilities and equipment 76.19%, customer contact items 88.6%). According to our ATP-based mothod, kitchen utensils (51 ± 45 RLU/25㎠) were relatively clean compared to other with facilities and equipment (167 ± 123 RLU/25㎠). In the present study, we also evaluated the usefulness of the ATP bioluminescence method for monitoring surface hygiene at hotel restaurants. After correlation analysis of surveillance of hygienic status points and ATP assay, most results showed negative and high correlation (-0.64--0.89). Our ATP assay (92 ± 67 RLU/25㎠) of each item after cleaning showed signigicantly reduced results compared to the ATP assay (1020 ± 1254 RLU/25㎠) for normal status, thereby indicating its suitability as a tool to verify the validity of cleaning. By our results, ATP bioluminescence could be used as an effective tool for visual numerical evaluation of invisible contaminants.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.27-42
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• 2020

Startup accelerators have emerged as new investment entities that help early startups, which are not easy to survive continuously due to lack of funds, commercialization capabilities, and experiences. As their positive performance on early startups and the ecosystem has been proven, the number of early startups which want to receive their investment is also increasing. However, they are vaguely preparing to attract accelerators' investment because they do not have any information on what factors the accelerators consider important. In addition, researches on startup accelerators are also at an early level, so there are no remarkable prior studies on factors that decide on investment. Therefore, this study aims to help startups prepare for investment attraction by looking at what factors are important for accelerators to invest, and to provide meaningful implications to academia. In the preceding study, we derived five upper level categories, 26 lower level accelerators' investment determinants through the qualitative meta-synthesis method, secondary data analysis, observation on US accelerators and in-depth interviews. In this study, we want to derive important implications by deriving priorities of the accelerators' investment determinants. Therefore, we used AHP that are evaluated as the suitable methodology for deriving importance and priority. The analysis results show that accelerators value market-related factors most. This means that startups that are subject to investment by accelerators are early-stage startups, and many companies have not fully developed their products or services. Therefore, market-related factors that can be evaluated objectively seem to be more important than products (or services) that are still ambiguous. Next, it was found that the factors related to the internal workforce of startups are more important. Since accelerators want to develop their businesses together with start-ups and team members through mentoring, ease of collaboration with them is very important, which seems to be important. The overall priority analysis results of the 26 investment determinants show that 'customer needs' and 'founders and team members' understanding of customers and markets' (0.62) are important and high priority factors. The results also show that startup accelerators consider the customer-centered perspective very important. And among the factors related to startups, the most prominent factor was the founder's openness and execution ability. Therefore, it can be confirmed that accelerators consider the ease of collaboration with these startups very important.

• Journal of Korea Port Economic Association
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• v.38 no.1
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• pp.1-14
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• 2022

The change in the management environment of the logistics industry in the era of global competition is becoming an era in which customers choose companies. Differentiation from competitors through the provision of products and services suitable for customers As customers' choices change depending on their superiority, companies are constantly striving to receive or retain customers' choices. Ultimately, this competitive structure can be seen as the importance of long-term relationship building. Therefore, in this study, we examined how factors related to transaction characteristics performed by logistics companies for customer satisfaction in the transaction relationship between cargo companies and shippers affect performance and long-term transaction intentions. First, we derived the factors of logistics service, cost, logistics infrastructure, and company competency, which are transaction characteristics factors of a logistics company that must be specifically realized for customer satisfaction in transactions between logistics companies. Second, we analyzed how the transaction characteristics factors of a logistics company affect the company's performance, and finally, how the company's performance factors affect long-term transaction intentions. As a result of empirical analysis, there were no statistically significant results on the relationship between transaction characteristics and performance of logistics companies, which can be attributed to the small size of the logistics companies that were the sample. In other words, logistics companies that do not have sufficient capacity to provide services at low prices have no choice but to engage in constant bleeding competition. It can be seen that it reflects the characteristics of the industry. On the other hand, the relationship between corporate performance factors and long-term transaction intention was found to have a positive relationship. The higher the level of partnership with logistics companies and visible financial performance is, the higher the transaction will be in the future, and the more the transaction volume will be gradually increased. And even if it costs a little more, it can be seen that the intention to continue trading is greatly expressed.

• Journal of Distribution Research
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• v.17 no.2
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• pp.1-28
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• 2012

I. Introduction : The purpose of this study is to test empirically hypothetical causality among constructs used in previous studies to build the model of relational market behavior on customers' participation and consumer-brand relationship after introducing theories of relationship marketing, loyalty program, consumer-brand relationship, customers' participation in service marketing as previous studies with regard to relational market behavior, which Bagozzi(1995) and Peterson(1995) commented on constructs and definition suggested by Sheth and Parvatiyar (1995). For this purpose, loyalty program by the service provider, customers' participation and consumer-brand relationship as preceding variables explain relational market behavior defined by Sheth and Parvatiyar(1995). This study proposes that loyalty program as a tool of relationship marketing will be effective in that consumers' participation in marketing relationship results in a narrow range of choice(Sheth and Parvatiyar, 1995) because consumers think that their participation motive result in benefits(Peterson, 1995). Also, it is proposed that the quality of consumer-brand relationship explain the performance of relationship as well as the intermediary effect because the loyalty program could be evaluated based on relationship with customers. We reviewed the variables with regard to performance of relationship based on relation maintain in marketing literature, and then tested our hypotheses related to several performance variables including loyalty and intention of relation maintain based on the previous studies and constructs(Bendapudi and Berry, 1997 ; Bettencourt, 1997 ; Palmatier, Dant, Grewal and Evans, 2006 ; You Jae Yi and Soo Jin Lee, 2006). II. Study Model : Analyses about hypothetical causality were proceeded. The marketing effect of loyalty program on relational market behavior was empirically tested in study regarding a service provider. The research model in according to the path hypotheses (loyalty program ${\rightarrow}$ customers' participation ${\rightarrow}$ consumer-brand relationship ${\rightarrow}$ relational market behavior and loyalty program ${\rightarrow}$ consumer-brand relationship, and loyalty program ${\rightarrow}$ relational market behavior and customers' participation ${\rightarrow}$ consumer-brand relationship, and customers' participation ${\rightarrow}$ relational market behavior) proceeded as an activity for customer relation management was suggested. The main purpose of study is to see if relational market behavior could be brought as a result of developing relationship between consumers and a corporate into being stronger and more valuable when a corporate or a service provider try aggressively to build the relationship with customers (Bettencourt, 1997; Palmatier, Dant, Grewal and Evans, 2006; Sheth and Parvatiyar, 1995). III. Conclusion : The results of research into the membership fitness club, one of service areas with high level of customer participation (Bitner, Faranda, Hubbert and Zeithaml, 1997; Chase, 1978; Kelley, Donnelly, Jr. and Skinner, 1990) are as follows: First, causalities in according to path hypotheses were tested, after the preceding variables affecting relational market behavior and conceptual frame were suggested. In study, all hypotheses were supported as expected. This result confirms the proposition suggested by Sheth and Parvatiyar(1995), who claimed that intention of consumer and corporate to participate in marketing relationship brings high level of marketing productivity. Also, as a corporate or a service provider try aggressively to build relationship with customers, the relationship between consumers and a corporate can be developed into stronger and more valuable one (Bettencourt, 1997; Palmatier, Dant, Grewal and Evans, 2006). This finding supports the logic of relationship marketing. Second, because the question regarding the path hypothesis of consumer-brand relationship ${\rightarrow}$ relational market behavior are still at issue, the further analyses were conducted. In particular, there existed the mediating effects of consumer-brand relationship toward relational market behavior. Also, multiple regressions were conducted to see if which one strongly influences relational market behavior among specific question items with regard to consumer-brand relationship. As a result, the influence between items composing consumer-brand relationship and ones composing relational market behavior was different. Among items composing consumer-brand relationship, intimacy was an influence of sustaining relationship, word of mouth, and recommendation, intimacy and interdependence were influences of loyalty, intimacy and self-connection were influences of tolerance and advice. Notably, commitment among items measuring consumer-brand relationship had the negative influence with relational market behavior. This means that bringing relational market behavior is not consumer-brand relationship without personal commitment, but effort to build customer relationship like intimacy, interdependence, and self-connection. This finding confirms the results of Breivik and Thorbjornsen(2008). They reported that six variables composing the quality of consumer-brand relationship have higher explanation in regression model directly affecting performance of consumer-brand relationship. As a result of empirical analysis, among the constructs with regard to consumer-brand relationship, intimacy(B=0.512), interdependence(B=0.196), and quality of partner(B=0.153) had the effects on relation maintain. On the contrary, self-connection, love and passion, and commitment had little effect and did not show the statistical significance(p<0.05). On the other hand, intimacy(B=0.668) and interdependence(B=0.181) had the high regression estimates on word of mouth and recommendation. Regarding the effect on loyalty, explanation level of the model was high(R2=0.515), intimacy(0.538), interdependence(0.223), and quality of partner(0.177) showed the statistical significance(p<0.05). Furthermore, intimacy(0.441) had the strong effect as well as self-connection(0.201) and interdependence (0.163) had the effect on tolerance and forgive. And these three variables showed effects even on advice and suggestion, intimacy(0.373), self-connection(0.270), interdependence (0.155) respectively. Third, in study with regard to the positive effect(loyalty program ${\rightarrow}$ customers' participation, loyalty program ${\rightarrow}$ consumer-brand relationship, loyalty program ${\rightarrow}$ relational market behavior, customers' participation ${\rightarrow}$ consumer-brand relationship, customers' participation ${\rightarrow}$ relational market behavior, consumer-brand relationship ${\rightarrow}$ relational market behavior), the path hypothesis of customers' participation ${\rightarrow}$ consumer-brand relationship, was supported. The fact that path hypothesis of customers' participation ${\rightarrow}$ consumer-brand relationship was supported confirms assertion by Bitner(1995), Fournier(1994), Sheth and Parvatiyar(1995) about consumer relationship to participate in marketing relationship.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Korean Academy of Nursing Administration
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• v.4 no.2
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• pp.307-319
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• 1998

This study is an empirical investigation and study on the measurement of nursing service quality as perceived by patients. A series of H1. H2. H3 alternative hypotheses were tested using a sample of 250 patients in Taegu City. Korea. HI hypothese were tested for application of five component of service quality (SERVQlTAL and SE RPERF : tangiblity. reliability. responsiveness. accessibility. understandability) in Taegu area Hospitals. Validity test - the five components of service quality were rearranged into two components of service quality (personal factor. nonpersonal factor). Although SERVQUAL was verified in USA. application for five components of service quality in Korea indicated that it need more analytical studies. Nobody can deny the fact that the recent growth of the nursing service quality is one of the most important driving forces of hospital management. In many hospitals. the nursing quality charges more than 50% of the medical service quality. As a result. many hospital managers should be enormous interests in the investment potentiality of the nursing service. However. doesn't many researchers invest their time and effort on the research of the quality control in nursing service. Nursing service management is the process to satisfy customer's desires and expectations through the various service activities. Presently nursing service are being faced with three Common tasks of improving quality of nursing service. competitively differential advantage and productivity because of quantitative expansion of Nursing service. Such a phenomenon is also found in our medical service industry. resulting from increasing demands for medical service owing to national medical insurance policy and consumer's attitude change emphasizing prevention of illness. excessiveness of medical facilities in large cities and increasing medical lawsuits due to influence of consumerism. Therefore. under such circumstances. this research on nursing service is conducted from nursing managements to improve the nursing service quality problems faced by medical institutions. The results of this theoretical/empirical research are as follows: 1. Nursing service Quality is regarded as patients' perceived quality and evaluated on the basis (5 dimension) of technical and functional quality. 2. Nursing service Quality is a concept of patients evaluation on the measurable multi-dimensions intrinsic and extrinsic attributes of service. 3. Nursing service Quality is conceptually defined as the difference between the perceived service and the expected service. 4. Korean consumers trend to evaluate nursing service quality based on such dimensions as responsiveness and reliability. understandability. accessibility. tangibility. 5. After analyzing whether or not there are some differences in respective medical institution. it was found that there are significant difference on understandability. reliability. communicability. courtesy. competence. 6. After analyzing the difference between the expected nursing service and the nursing perceived service, it was found that the expected nursing service is higher than the perceived service in every medical institution. 7. HI hypothesis was tested with regard to the validity test between SERVQUAL and SERVPERF in nursing service quality. The result of validity test between SERVQUAL and SERVPERF was found to have differential result. That is the R2 of SERVPERF is higher than that of SERVQUAL. Therefore. HI was verified in nursing management. H2. H3 hypotheses were tested whether or not the nursing service quality and patient satisfaction is the preceding variable. The result of H2 hypothes is that the nursing service quality is the preceding variable of patient satisfaction and the patient satisfaction is that of revisiting intention. After analyzing whether or not there is any differences on the demographic variable of five nursing service quality factor. it was found that there are statistically significant differences on communicability and courtesy at the sex. understand ability. accessibility and tangibility at the age. understandability at the academic background respectively.

• The Journal of Industrial Distribution & Business
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• v.3 no.1
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• pp.7-16
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• 2012

Despite the enforcement of SSM control laws such as 'the Law of Developing the Distribution Industry (LDDI)' and 'the Law of Promoting Mutual Cooperation between Large and Small/medium Enterprises (LPMC)' stipulating the business adjustment system, the number of super-supermarkets (SSMs) has ever been expanding in Korea. In France, however, Super Centers are being regulated most strongly and directly in the whole Europe viewing that there is not a single SSM in Paris, which is emphasized to be the outcome from French government's regulation exerted on the opening of large scale retail stores. In France, the authority to approve store opening is deeply centralized and the store opening regulation is a socio-economic regulation driven by economic laws whereas EU strongly regulates the distribution industry. To control the French distribution industry, such seven laws and regulations as Commission départementale d'urbanisme commercial guidelines (CDLIC) (1969), the Royer Law (1973), the Doubin Law (1990), the Sapin Law (1993), the Raffarin Law (1996), solidarite et renouvellement urbains (SRU) (2000), and Loi de modernisation de l'économie (LME) (2009) have been promulgated one by one since the amendment of the Fontanet guidelines, through which commercial adjustment laws and regulations have been complemented and reinforced while regulatory measures have been taken. Even in the course of forming such strong regulatory laws, InterMarche, the largest supermarket chain in France, has been in existence as a global enterprise specialized in retail distribution with over 4,000 stores in Europe. InterMarche's business can be divided largely into two segments of food and non-food. As a supermarket chain, InterMarche's food segment has 2,300 stores in Europe and as a hard-discounter store chain in France, Netto has 420 stores. Restaumarch is a chain of traditional family restaurants and the steak house restaurant chain of Poivre Rouge has 4 restaurants currently. In addition, there are others like Ecomarche which is a supermarket chain for small and medium cities. In the non-food segment, the DIY and gardening chain of Bricomarche has a total of 620 stores in Europe. And the car-related chain of Roady has a total of 158 stores in Europe. There is the clothing chain of Veti as well. In view of InterMarche's management strategies, since its distribution strategy is to sell goods at cheap prices, buying goods cheap only is not enough. In other words, in order to sell goods cheap, it is all important to buy goods cheap, manage them cheap, systemize them cheap, and transport them cheap. In quality assurance, InterMarche has guaranteed the purchase safety for consumers by providing its own private brand products. InterMarche has 90 private brands of its own, thus being the retailer with the largest number of distributor brands in France. In view of its IT service strategy, InterMarche is utilizing a high performance IT system so as to obtainas much of the market information as possible and also to find out the best locations for opening stores. In its global expansion strategy of international alliance, InterMarche has established the ALDIS group together with the distribution enterprises of both Spain and Germany in order to expand its food purchase, whereas in the non-food segment, it has established the ARENA group in alliance with 11 international distribution enterprises. Such strategies of InterMarche have been intended to find out the consumer needs for both price and quality of goods and to secure the purchase and supply networks which are closely localized. It is necessary to cope promptly with the constantly changing circumstances through being unified with relevant regions and by providing diversified customer services as well. In view of the InterMarche's positive policy for promoting local partnerships as well as the assistance for enhancing the local economic structure, implications are existing for those retail distributors of our country.