• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.219-240
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• 2018

Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of the Korean Wood Science and Technology
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• v.2 no.4
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• pp.4-14
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• 1974

The total forest land area in Korea accounts for some 67 percent of the nation's land total. Its productivity, however, is very low. Consequently, forest production accounts for only about 2 percent of the gross national product and a minor proportion of no more than about 5 percent versus primary industry. In this case, however, only the direct income from forestry is taken into account, making no reference to the forestry output induced by other industrial sectors. The value added Or the induced forestry output in manufacturing the primary wood products into higher quality products, makes a larger contribution to the economy than direct contribution. So, this author has tried to analyze the structure of forestry and compute the repercussion effect and the induced output of primary forest products when utilized by other industries for their raw materials, Hsing the input-output table and attached tables for 1963 and 1966 issued by the Bank of Korea. 1. Analysis of forestry structure A. Changes in total output Durng the nine-year period, 1961-1969, the real gross national product in Korea increased 2.1 times, while that of primary industries went up about 1. 4 times. Forestry which was valued at 9,380 million won in 1961, was picked up about 2. 1 times to 20, 120 million won in 1969. The rate of the forestry income in the GNP, accordingly, was no more than 1.5 percent both in 1961 and 1962, whereas its rate in primary industries increased 3.5 to 5.4 percent. Such increase in forestry income is attributable to increased forest production and rise in timber prices. The rate of forestry income, nonetheless, was on the decrease on a gradual basis. B. Changes in input coefficient The input coefficient which indicates the inputs of the forest products into other sectors were up in general in 1966 over 1963. It is noted that the input coefficient indicating the amount of forest products supplied to such industries closely related with forestry as lumber and plywood, and wood products and furniture, showed a downward trend for the period 1963-1966. On the other hand, the forest input into other sectors was generally on the increase. Meanwhile, the input coefficient representing the yolume of the forest products supplied to the forestry sector itself showed an upward tendency, which meant more and more decrease in input from other sectors. Generally speaking, in direct proportion to the higher input coefficient in any industrial sector, the reinput coefficient which denotes the use of its products by the same sector becomes higher and higher. C. Changes in ratio of intermediate input The intermediate input ratio showing the dependency on raw materials went up to 15.43 percent m 1966 from 11. 37 percent in 1963. The dependency of forestry on raw materials was no more than 15.43 percent, accounting for a high 83.57 percent of value added. If the intermediate input ratio increases in any given sector, the input coefficient which represents the fe-use of its products by the same sector becomes large. D. Changes in the ratio of intermediate demand The ratio of the intermediate demand represents the characteristics of the intermediary production in each industry, the intermediate demand ratio in forestry which accunted for 69.7 percent in 1963 went up to 75.2 percent in 1966. In other words, forestry is a remarkable industry in that there is characteristics of the intermediary production. E. Changes in import coefficient The import coefficient which denotes the relation between the production activities and imports, recorded at 4.4 percent in 1963, decreased to 2.4 percent in 1966. The ratio of import to total output is not so high. F. Changes in market composition of imported goods One of the major imported goods in the forestry sector is lumber. The import value increased by 60 percent to 667 million won in 1966 from 407 million won in 1963. The sales of imported forest products to two major outlets-lumber and plywood, and wood products and furniture-increased to 343 million won and 31 million won in 1966 from 240million won and 30 million won in 1963 respectively. On the other hand, imported goods valued at 66 million won were sold to the paper products sector in 1963; however, no supply to this sector was recorded in 1963. Besides these major markets, primary industries such as the fishery, coal and agriculture sectors purchase materials from forestry. 2. Analysis of repercussion effect on production The repercussion effect of final demand in any given sector upon the expansion of the production of other sectors was analyzed, using the inverse matrix coefficient tables attached to the the I.O. Table. A. Changes in intra-sector transaction value of inverse matrix coefficient. The intra-sector transaction value of an inverse matrix coefficient represents the extent of an induced increase in the production of self-support products of the same sector, when it is generated directly and indirectly by one unit of final demand in any given sector. The intra-sector transaction value of the forestry sector rose from 1.04 in 1963 to 1, 11 in 1966. It may well be said, therefore, that forestry induces much more self-supporting products in the production of one unit of final demand for forest products. B. Changes in column total of inverse matrix coefficient It should be noted that the column total indicates the degree of effect of the output of the corresponding and related sectors generated by one unit of final demand in each sector. No changes in the column total of the forestry sector were recorded between the 1963 and 1966 figures, both being the same 1. 19. C. Changes in difference between column total and intra-sector transaction amount. The difference between the column total and intra-sector transaction amount by sector reveals the extent of effect of output of related industrial sector induced indirectly by one unit of final demand in corresponding sector. This change in forestry dropped remarkable to 0.08 in 1966 from 0.15 in 1963. Accordingly, the effect of inducement of indirect output of other forestry-related sectors has decreased; this is a really natural phenomenon, as compared with an increasing input coefficient generated by the re-use of forest products by the forestry sector. 3. Induced output of forestry A. Forest products, wood in particular, are supplied to other industries as their raw materials, increasng their value added. In this connection the primary dependency rate on forestry for 1963 and 1966 was compared, i. e., an increase or decrease in each sector, from 7.71 percent in 1963 to 11.91 percent in 1966 in agriculture, 10.32 to 6.11 in fishery, 16.24 to 19.90 in mining, 0.76 to 0.70 in the manufacturing sector and 2.79 to 4.77 percent in the construction sector. Generally speaking, on the average the dependency on forestry during the period 1963-1966 increased from 5.92 percent to 8.03 percent. Accordingly, it may easily be known that the primary forestry output induced by primary and secondary industries increased from 16, 109 million won in 1963 to 48, 842 million won in 1966. B. The forest products are supplied to other industries as their raw materials. The products are processed further into higher quality products. thus indirectly increasing the value of the forest products. The ratio of the increased value added or the secondary dependency on forestry for 1963 and 1966 showed an increase or decrease, from 5.98 percent to 7.87 percent in agriculture, 9.06 to 5.74 in fishery, 13.56 to 15.81 in mining, 0.68 to 0.61 in the manufacturing sector and 2.71 to 4.54 in the construction sector. The average ratio in this connection increased from 4.69 percent to 5.60 percent. In the meantime, the secondary forestry output induced by primary and secondary industries rose from 12,779 million Wall in 1963 to 34,084 million won in 1966. C. The dependency of tertiary industries on forestry showed very minor ratios of 0.46 percent and 0.04 percent in 1963 and 1966 respectively. The forestry output induced by tertiary industry also decreased from 685 million won to 123 million won during the same period. D. Generally speaking, the ratio of dependency on forestry increased from 17.68 percent in 1963 to 24.28 percent in 1966 in primary industries, from 4.69 percent to 5.70 percent in secondary industries, while, as mentioned above, the ratio in the case of tertiary industry decreased from 0.46 to 0.04 percent during the period 1963-66. The mining industry reveals the heaviest rate of dependency on forestry with 29.80 percent in 1963 and 35.71 percent in 1966. As it result, the direct forestry income, valued at 8,172 million won in 1963, shot up to 22,724 million won in 1966. Its composition ratio lo the national income rose from 1.9 percent in 1963 to 2.3 per cent in 1966. If the induced outcome is taken into account, the total forestry production which was estimated at 37,744 million won in 1963 picked up to 105,773 million won in 1966, about 4.5 times its direct income. It is further noted that the ratio of the gross forestry product to the gross national product. rose significantly from 8.8 percent in 1963 to 10.7 percent in 1966. E. In computing the above mentioned ratio not taken into consideration were such intangible, indirect effects as the drought and flood prevention, check of soil run-off, watershed and land conservation, improvement of the people's recreational and emotional living, and maintenance and increase in the national health and sanitation. F. In conclusion, I would like to emphasize that the forestry sector exercices an important effect upon the national economy and that the effect of induced forestry output is greater than its direct income.

• Journal of Nutrition and Health
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• v.6 no.1
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• pp.71-76
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• 1973

1. This survey is somewhat different from that conducted by Yonsei University, although being in many respects, very similar. We found the average per capita caloric intake to be 7 or 8% of what it should be. Of that caloric intake, 84.5% in the model village here and 82.2% in the compared village Bupyong, by and large depends on cereal grains. Since such grains tend to distend the stomach, the farmers, it seems,should substitute fat for a part of their diet so as to dimish digestive pain and still receive the necessary calories. 2. Protein is the most important nutrient for the development of physical strength and improvement of health, but the average daily intake is only 68.3% of the necessary amount. It is desirable that the ratio of vegetable protein to that of animal be one to three for maintaining one's health. Most of the villager's protein, however, comes from plants: the intake of animal protein, at a level of only 13.6 g, is far below such a one to three ratio. 3. In the model village, 497.6 mg, of inorganic calcium is the daily intake level. In the compared village it is 505.5 mg, making a difference of only 8mg. This, however, is 35% less than the recommended intake. More than 50% of this calcium comes from cereals and other plants. Moreover, plant calcium which has much oxakuc acud us not as nutritional as animal calcium, so their calcium diet is less than it would appear. We must, therefore, make efforts to receive as good nutritional calcium as possible. 4. Among the vitamin group, the daily average intake of vitamin A and vitamin $B_{2}$ are respectively 40% and 32% less than the desired intake, while vitamin $B_{1}$ happens to be taken in sufficient quantities and more niacin is taken than which is even necessary. The intake of vitamin C is much more than the necessary quantity. However, this figure was calculated from uncooked food; if the loss from cooking were to be considered, the real intake might well be a little less. Also, as this survey was carried out in May, some of these results were influenced by the fact that lettuce and spinach are seasonally popular. In conclusion, except for a few nutrients which are in abundance, the normal food intake in a day is, on the whole, less than the average recommended. Furthermore despite the fact that both of these places are model villages in the development of nutrition, it seems that they have not gotten out of such conventional eating habiys as the almost dependancy on cereal grains. Cow's milk, sheep's milk, eggs and so on produced by each farmhouse are not used for their own families but are taken to the market for the purpose of making money. Accordingly, I think from now we must seek to improve, guide and enlighten the farmers as to how to correct their eating habits and implement changes in their lives so that our firm purpose may be achieved.

• Journal of Distribution Science
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• v.10 no.3
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• pp.51-61
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• 2012

This study seeks to understand how the choice of a coffee shop is related to a customer's loyalty and which characteristics of a shop influence this choice. It considers large-sized coffee shops brands whose market scale has gradually grown. The users' choice of shop is determined by price, employee service, shop location, and shop atmosphere. The study investigated the effects of these four properties on the brand attitudes of coffee shops. The effects were found to vary depending on users' characteristics. The properties with the largest influence were shop atmosphere and shop location Therefore, the purpose of the study was to examine the properties that could help coffee shops get loyal customers, and the choice properties that could satisfy consumers' desires The study examined consumers' perceptions of shop properties at selection of coffee shop and the difference between perceptual difference and coffee brand in order to investigate customers' desires and needs and to suggest ways that could supply products and service. The research methodology consisted of two parts: normative and empirical research, which includes empirical analysis and statistical analysis. In this study, a statistical analysis of the empirical research was carried out. The study theoretically confirmed the shop choice properties by reviewing previous studies and performed an empirical analysis including cross tabulation based on secondary material. The findings were as follows: First, coffee shop choice properties varied by gender. Price advantage influenced the choice of both men and women; men preferred nearer coffee shops where they could buy coffee easily and more conveniently than women did. The atmosphere of the coffee shop had the greatest influence on both men and women, and shop atmosphere was thought to be the most important for age analysis. In the past, customers selected coffee shops solely to drink coffee. Now, they select the coffee shop according to its interior, menu variety, and atmosphere owing to improved quality and service of coffee shop brands. Second, the prices of the brands did not vary much because the coffee shops were similarly priced. The service was thought to be more important and to elevate service quality so that price and employee service and other properties did not have a great influence on shop choice. However, those working in the farming, forestry, fishery, and livestock industries were more concerned with the price than the shop atmosphere. College and graduate school students were also affected by inexpensive price. Third, shop choice properties varied depending on income. The shop location and shop atmosphere had a greater influence on shop choice. The customers in an income bracket of less than 2 million won selected low-price coffee shops more than those earning 6 million won or more. Therefore, price advantage had no relation with difference in income. The higher income group was not affected by employee service. Fourth, shop choice properties varied depending on place. For instance, customers at Ulsan were the most affected by the price, and the ones at Busan were the least affected. The shop location had the greatest influence among all of the properties. Among the places surveyed, Gwangju had the least influence. The alternate use of space in a coffee shop was thought to be important in all the cities under consideration. The customers at Ulsan were not affected by employee service, and they selected coffee shops according to quality and preference of shop atmosphere. Lastly, the price factor was found to be a little higher than other factors when customers frequently selected brands according to shop properties. Customers at Gwangju reacted to discounts more than those in other cities did, and the former gave less priority to the quality and taste of coffee. Brand preference varied depending on coffee shop location. Customers at Busan selected brands according to the coffee shop location, and those at Ulsan were not influenced by employee kindness and specialty. The implications of this study are that franchise coffee shop businesses should focus on customers rather than aggressive marketing strategies that increase the number of coffee shops. Thus, they should create an environment with a good atmosphere and set up coffee shops in places that customers have good access to. This study has some limitations. First, the respondents were concentrated in metropolitan areas. Secondary data showed that the number of respondents at Seoul was much more than that at Gyeonggi-do. Furthermore, the number of respondents at Gyeonggi-do was much more than those at the six major cities in the nation. Thus, the regional sample was not representative enough of the population. Second, respondents' ratio was used as a measurement scale to test the perception of shop choice properties and brand preference. The difficulties arose when examining the relation between these properties and brand preference, as well as when understanding the difference between groups. Therefore, future research should seek to address some of the shortcomings of this study: If the coffee shops are being expanded to local areas, then a questionnaire survey of consumers at small cities in local areas shall be conducted to collect primary material. In particular, variables of the questionnaire survey shall be measured using Likert scales in order to include perception on shop choice properties, brand preference, and repurchase. Therefore, correlation analysis, multi-regression, and ANOVA shall be used for empirical analysis and to investigate consumers' attitudes and behavior in detail.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.59-69
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• 2010

Green or an environmental consciousness has been a major issue for businesses and government offices, as well as consumers, worldwide. In response to this movement, the Korean government announced, in the early 2000s, the era of "Green Growth" as a way to encourage green-related business activities. The Korean fashion industry, in various levels of involvement, presents diverse eco-friendly products as a part of the green movement. These apparel products include organic products and recycled clothing. For these companies to be successful, they need information about who are the consumers who consider green issues (e.g., environmental sustainability) as part of their personal values when making a decision for product purchase, use, and disposal. These consumers can be considered as eco-sumers. Previous studies have examined consumers' purchase intention for or with eco-friendly products. In addition, studies have examined influential factors used to identify the eco-sumers or green consumers. However, limited attention was paid to eco-sumers' disposal or recycling behavior of clothes in comparison with their green product purchases. Clothing disposal behaviors are ways that consumer can get rid of unused clothing and in clue temporarily lending the item or permanently eliminating the item by "handing down" (e.g., giving it to a younger sibling), donating, exchanging, selling, or simply throwing it away. Accordingly, examining purchasing behaviors of eco-friendly fashion items in conjunction with clothing disposal behaviors should improve understanding of a consumer's clothing consumption behavior from the environmental perspective. The purpose of this exploratory study is to provide descriptive information about Korean eco-sumers who have ecologically-favorable lifestyles and behaviors when buying and disposing of clothes. The objectives of this study are to (a) categorize Koreans on the basis of clothing disposal behaviors; (b) investigate the differences in demographics, lifestyles, and clothing consumption values among segments; and (c) compare the purchase intention of eco-friendly fashion items and influential factors among segments. A self-administered questionnaire was developed based on previous studies. The questionnaire included 10 items of clothing disposal behavior, 22 items of LOHAS (Lifestyles of Health and Sustainability) characteristics, and 19 items of consumption values, measured by five-point Likert-type scales. In addition, the purchase intention of two eco-friendly fashion items and 11 attributes of each item were measured by seven-point Likert type scales. Two polyester fleece pullovers, made from fabric created from recycled bottles with the PET identification code, were selected from one Korean brand and one US imported brand among outdoor sportswear brands. A brief description of each product with a color picture was provided in the survey. Demographic variables (i.e., gender, age, marital status, education level, income, occupation) were also included. The data were collected through a professional web survey agency during May 2009. A total of 600 final usable questionnaires were analyzed. The age of respondents ranged from 20 to 49 years old with a mean age of 34 years. Fifty percent of the respondents were males and about 58% were married, and 62% reported having earned university degrees. Principal components factor analysis with varimax rotation was used to identify the underlying dimensions of the clothing disposal behavior scale, and three factors were generated (i.e., reselling behavior, donating behavior, non-recycling behavior). To categorize the respondents on the basis of clothing disposal behaviors, k-mean cluster analysis was used, and three segments were obtained. These consumer segments were labeled as 'Resale Group', 'Donation Group', and 'Non-Recycling Group.' The classification results indicated approximately 98 percent of the original cases were correctly classified. With respect to demographic characteristics among the three segments, significant differences were found in gender, marital status, occupation, and age. LOHAS characteristics were reduced into the following five factors: self-satisfaction, family orientation, health concern, environmental concern, and voluntary service. Significant differences were found in the LOHAS factors among the three clusters. Resale Group and Donation Group showed a similar predisposition to LOHAS issues while the Non-Recycling Group presented the lowest mean scores on the LOHAS factors compared to the other segments. The Resale and Donation Groups described themselves as enjoying or being satisfied with their lives and spending spare-time with family. In addition, these two groups cared about health and organic foods, and tried to conserve energy and resources. Principal components factor analysis generated clothing consumption values into the following three factors: personal values, social value, and practical value. The ANOVA test with the factors showed differences primarily between the Resale Group and the other two groups. The Resale Group was more concerned about personal value and social value than the other segments. In contrast, the Non-Recycling Group presented the higher level of social value than did Donation Group. In a comparison of the intention to purchase eco-friendly products, the Resale Group showed the highest mean score on intent to purchase Product A. On the other hand, the Donation Group presented the highest intention to purchase for Product B among segments. In addition, the mean scores indicated that the Korean product (Product B) was more preferable for purchase than the U.S. product (Product A). Stepwise regression analysis was used to identify the influence of product attributes on the purchase intention of eco product. With respect to Product A, design, price and contribution to environmental preservation were significant to predict purchase intention for the Resale Group, while price and compatibility with my image factors were significant for the Donation Group. For the Non-Recycling Group, design, price compatibility with the factors of my image, participation to eco campaign, and contribution to environmental preservation were significant. Price appropriateness was significant for each of the three clusters. With respect to Product B, design, price and compatibility with my image factors were important, but different attributes were associated significantly with purchase intention for each of the three groups. The influence of LOHAS characteristics and clothing consumption values on intention to purchase Products A and B were also examined. The LOHAS factor of health concern and the personal value factor were significant in the relationships with the purchase intention; however, the explanatory powers were low in the three segments. Findings showed that each group as classified by clothing disposal behaviors showed differences in the attributes of a product, personal values, and the LOHAS characteristics that influenced their purchase intention of eco-friendly products. Findings would enable organizations to understand eco-friendly behavior and to design appropriate strategic decisions to appeal eco-sumers.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.32-43
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• 2009

Trust has been studied extensively in psychology, economics, and sociology, and its importance has been emphasized not only in marketing, but also in business disciplines in general. Unlike past relationships between suppliers and buyers, which take considerable advantage of private networks and may involve unethical business practices, partnerships between suppliers and buyers are at the core of success for industrial marketing amid intense global competition in the 21st century. A high level of mutual cooperation occurs through an exchange relationship based on trust, which brings long-term benefits, competitive enhancements, and transaction cost reductions, among other benefits, for both buyers and suppliers. In spite of the important role of trust, existing studies in buy-supply situations overlook the role of trust and do not systematically analyze the effect of trust on relational performance. Consequently, an in-depth study that determines the relation of trust to the relational performance between buyers and suppliers of business services is absolutely needed. Business services in this study, which include those supporting the manufacturing industry, are drawing attention as the economic growth engine for the next generation. The Korean government has selected business services as a strategic area for the development of manufacturing sectors. Since the demands for opening business services markets are becoming fiercer, the competitiveness of the business service industry must be promoted now more than ever. The purpose of this study is to investigate the effect of the mutual trust between buyers and suppliers on relational performance. Specifically, this study proposed a theoretical model of trust-relational performance in the transactions of business services and empirically tested the hypotheses delineated from the framework. The study suggests strategic implications based on research findings. Empirical data were collected via multiple methods, including via telephone, mail, and in-person interviews. Sample companies were knowledge-based companies supplying and purchasing business services in Korea. The present study collected data on a dyadic basis. Each pair of sample companies includes a buying company and its corresponding supplying company. Mutual trust was traced for each pair of companies. This study proposes a model of trust-relational performance of buying-supplying for business services. The model consists of trust and its antecedents and consequences. The trust of buyers is classified into trust toward the supplying company and trust toward salespersons. Viewing trust both at the individual level and the organizational level is based on the research of Doney and Cannon (1997). Normally, buyers are the subject of trust, but this study supposes that suppliers are the subjects. Hence, it uniquely focused on the bilateral perspective of perceived risk. In other words, suppliers, like buyers, are the subject of trust since transactions are normally bilateral. From this point of view, suppliers' trust in buyers is as important as buyers' trust in suppliers. The suppliers' trust is influenced by the extent to which it trusts the buying companies and the buyers. This classification of trust using an individual level and an organization level is based on the suggestion of Doney and Cannon (1997). Trust affects the process of supplier selection, which works in a bilateral manner. Suppliers are actively involved in the supplier selection process, working very closely with buyers. In addition, the process is affected by the extent to which each party trusts its partners. The selection process consists of certain steps: recognition, information search, supplier selection, and performance evaluation. As a result of the process, both buyers and suppliers evaluate the performance and take corrective actions on the basis of such outcomes as tangible, intangible, and/or side effects. The measurement of trust used for the present study was developed on the basis of the studies of Mayer, Davis and Schoorman (1995) and Mayer and Davis (1999). Based on their recommendations, the three dimensions of trust used for the study include ability, benevolence, and integrity. The original questions were adjusted to the context of the transactions of business services. For example, a question such as "He/she has professional capabilities" has been changed to "The salesperson showed professional capabilities while we talked about our products." The measurement used for this study differs from those used in previous studies (Rotter 1967; Sullivan and Peterson 1982; Dwyer and Oh 1987). The measurements of the antecedents and consequences of trust used for this study were developed on the basis of Doney and Cannon (1997). The original questions were adjusted to the context of transactions in business services. In particular, questions were developed for both buyers and suppliers to address the following factors: reputation (integrity, customer care, good-will), market standing (company size, market share, positioning in the industry), willingness to customize (product, process, delivery), information sharing (proprietary information, private information), willingness to maintain relationships, perceived professionalism, authority empowerment, buyer-seller similarity, and contact frequency. As a consequential variable of trust, relational performance was measured. Relational performance is classified into tangible effects, intangible effects, and side effects. Tangible effects include financial performance; intangible effects include improvements in relations, network developing, and internal employee satisfaction; side effects include those not included either in the tangible or intangible effects. Three hundred fifty pairs of companies were contacted, and one hundred five pairs of companies responded. After deleting five company pairs because of incomplete responses, one hundred five pairs of companies were used for data analysis. The response ratio of the companies used for data analysis is 30% (105/350), which is above the average response ratio in industrial marketing research. As for the characteristics of the respondent companies, the majority of the companies operate service businesses for both buyers (85.4%) and suppliers (81.8%). The majority of buyers (76%) deal with consumer goods, while the majority of suppliers (70%) deal with industrial goods. This may imply that buyers process the incoming material, parts, and components to produce the finished consumer goods. As indicated by their report of the length of acquaintance with their partners, suppliers appear to have longer business relationships than do buyers. Hypothesis 1 tested the effects of buyer-supplier characteristics on trust. The salesperson's professionalism (t=2.070, p<0.05) and authority empowerment (t=2.328, p<0.05) positively affected buyers' trust toward suppliers. On the other hand, authority empowerment (t=2.192, p<0.05) positively affected supplier trust toward buyers. For both buyers and suppliers, the degree of authority empowerment plays a crucial role in the maintenance of their trust in each other. Hypothesis 2 tested the effects of buyerseller relational characteristics on trust. Buyers tend to trust suppliers, as suppliers make every effort to contact buyers (t=2.212, p<0.05). This tendency has also been shown to be much stronger for suppliers (t=2.591, p<0.01). On the other hand suppliers trust buyers because suppliers perceive buyers as being similar to themselves (t=2.702, p<0.01). This finding confirmed the results of Crosby, Evans, and Cowles (1990), which reported that suppliers and buyers build relationships through regular meetings, either for business or personal matters. Hypothesis 3 tested the effects of trust on perceived risk. It has been found that for both suppliers and buyers the lower is the trust, the higher is the perceived risk (t=-6.621, p<0.01 for buyers; t=-2.437, p<0.05). Interestingly, this tendency has been shown to be much stronger for buyers than for suppliers. One possible explanation for this higher level of perceived risk is that buyers normally perceive higher risks than do suppliers in transactions involving business services. For this reason, it is necessary for suppliers to implement risk reduction strategies for buyers. Hypothesis 4 tested the effects of trust on information searching. It has been found that for both suppliers and buyers, contrary to expectation, trust depends on their partner's reputation (t=2.929, p<0.01 for buyers; t=2.711, p<0.05 for suppliers). This finding shows that suppliers with good reputations tend to be trusted. Prior experience did not show any significant relationship with trust for either buyers or suppliers. Hypothesis 5 tested the effects of trust on supplier/buyer selection. Unlike buyers, suppliers tend to trust buyers when they think that previous transactions with buyers were important (t=2.913 p<0.01). However, this study did not show any significant relationship between source loyalty and the trust of buyers in suppliers. Hypothesis 6 tested the effects of trust on relational performances. For buyers and suppliers, financial performance reportedly improved when they trusted their partners (t=2.301, p<0.05 for buyers; t=3.692, p<0.01 for suppliers). It is interesting that this tendency was much stronger for suppliers than it was for buyers. Similarly, competitiveness was reported to improve when buyers and suppliers trusted their partners (t=3.563, p<0.01 for buyers; t=3.042, p<0.01 for suppliers). For suppliers, efficiency and productivity were reportedly improved when they trusted buyers (t=2.673, p<0.01). Other performance indices showed insignificant relationships with trust. The findings of this study have some strategic implications. First and most importantly, trust-based transactions are beneficial for both suppliers and buyers. As verified in the study, financial performance can be improved through efforts to build and maintain mutual trust. Similarly, competitiveness can be increased through the same kinds of effort. Second, trust-based transactions can facilitate the reduction of perceived risks inherent in the purchasing situation. This finding has implications for both suppliers and buyers. It is generally believed that buyers perceive higher risks in a highly involved purchasing situation. To reduce risks, previous studies have recommended that suppliers devise risk-reducing tactics. Moving beyond these recommendations, the present study uniquely focused on the bilateral perspective of perceived risk. In other words, suppliers are also susceptible to perceived risks, especially when they supply services that require very technical and sophisticated manipulations and maintenance. Consequently, buyers and suppliers must solve problems together in close collaboration. Hence, mutual trust plays a crucial role in the problem-solving process. Third, as found in this study, the more authority a salesperson has, the more he or she can be trusted. This finding is very important with regard to tactics. Building trust is a long-term assignment; however, when mutual trust has not been developed, suppliers can overcome the problems they encounter by empowering a salesperson with the authority to make certain decisions. This finding applies to suppliers as well.