• 한국산림과학회지
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• 제13권1호
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• pp.25-39
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• 1971

약배양(葯培養)에 의(依)한 반수체식물(半數體植物)의 유기(誘起)가 돌연변이(突然變異), 유전학등(遺傳學等)의 기초연구(基礎硏究)나 실지육종사업(實地育種事業)에 혁신(革新)을 갖져올 수 있다는 사실(事實)이 알려지자 최근(最近) 2-3년간(年間) 이에 대(對)하여 많은 연구(硏究)가 시도(試圖)되었지만 현재(現在)까지 성공(成功)된 식물(植物)의 종류(種類)는 수종(數種)에 불과(不過)하다. 식물(植物)의 여러조직배양법(組織培養法) 중(中)에서도 약배양(葯培養)이 특(特)히 힘든것은 이 경우(境遇)에는 환원소포자(還元小胞子)에서 Callus가 embryoid를 유기(誘起)하여야만 되기 때문이다. 과수(果樹)와 화목류(花木類) 4속(屬) 7종(種)의 식물(植物)을 대상(對象)으로 약배양(葯培養)을 시도(試圖)하였다. 배양약(培養葯)은 대개(大槪) 4분자(分子)에서 늦은 소포자기(小胞子期)의 것을 혼합(混合)하여 사용(使用)하였고 배양기(培養基)는 Modified murashige and skoog의 배지(培地)를 기본배지(基本培地)로 하고 여기에 NAA, $2{\cdot}4$-D, YE, Kinetin등(等) 생장조절물질(生長調節物質)을 농도(濃度)와 조합(組合)을 달리한것을 첨가(添加)하여 만들었다. 재료(材料)의 취급(取扱), 멸균배양(滅菌培養)에 따른 여러조작(操作), 조직표본작성등(組織標本作成等) 모든것은 상법(常法)에 의(依)하였다. 이제 성적(成績)을 요약(要略)하면 다음과 같다. 1. Callus는 개나리, 진달래, 산철쭉, 살구 등(等)에서 형성(形成)되었고 복숭아, 배, 자두에서는 안생긴다. 2. Auxin Kinetin의 종류(種類)와 농도(濃度)를 달리한 여러 배양기(培養基)를 사용(使用)하였지만 Callus형성(形成)은 어느 것에서나 잘된다. 3. 개나리에서는 Callus는 약표면(葯表面), 약격부위(葯隔部位)에서 체세포기원(體細胞起源)의 2배성(倍性) Callus가 생기고 소포자(小胞子)에서는 안생긴다. 오래 배양(培養)된 소포자(小胞子)에서는 대부분(大部分) 전분(澱粉)이 축적(蓄積)된다. 4. 진달래에서는 화사(花絲), 약격(葯隔), 약내동(葯內童) 등(等)에서 체세포성(體細胞性) Callus가 형성(形成)되고 소포자기원(小胞子期源)의 Callus는 안생기고 소포자(小胞子)에는 전분(澱粉)이 축적(蓄積)된다. 5. 산철쭉은 Callus형성(形成)이 화사(花絲), 약격등(葯隔等)에서도 생기지만 주(主)로 화사반대편(花絲反對便)의 약이첨단(葯耳尖端)에서 잘생긴다. 소포자기원(小胞子期源)의 Callus는 안생기고 소포자(小胞子) 전분(澱粉)이 축적(蓄積)되는 점(點)은 진달래와 같다. 6. 살구는 체세포성(體細胞性) 약조직기원(葯組織起源)의 Callus는 거이 안생기고 Callus는 약강내부(葯腔內部)에서 형성(形成)되어 약봉합부(葯縫合部)를 헤치고 나온다. 오래 배양(培養)된 소포자(小胞子)에도 전분(澱粉)은 축적(蓄積)되지 않는다. 7. 복숭아, 배, 자두 들에서는 60여일배양(餘日培養)된 약(葯)의 어느 부위(部位)에서도 Callus는 형성(形成)되지 않는다. 반면(反面) 소포자(小胞子)에 전분축적(澱粉蓄積)도 안되는것이 특징(特徵)이다. 8. 체세포(體細胞) Callus는 주(主)로 약벽내피(葯壁內被), 두 약강(葯腔)사이의 격막(隔膜), 약격(葯隔) 및 약이유조직등(葯耳柔組織等)에서 생긴다. 9. 살구의 약조직(葯組織)은 배양중(培養中) 별(別)로 변화(變化)가 안되지만 소포자(小胞子)는 변화(變化)하야 다핵소포자(多核小胞子), 다조포체(多組胞體)들이 약강내(葯腔內)에 출현(出現)한다. 이런 현상(現像)은 살구의 Callus는 소포자기원(小胞子期源) 이라는것을 표시(表示)해준다. 10. 7종(種)의 식물중(植物中) 살구만은 환원성(還元性) 소포자(小胞子) Callus가 생기고 기타(基他)의 식물(植物)들은 약(葯)의 체세포성(體細胞性) 조직(組織)에서 Callus가 형성(形成)되기 때문에 반수체육종(半數體育種)의 가능성(可能性)은 살구에서만 있다.

• 한국학교ㆍ지역보건교육학회지
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• 제3권
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• pp.111-140
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• 2002

This study was conducted from April 1 through April 30, 2002 in order to figure out the relationship between physical health status and life style and the factors influencing physical health. Subjects were selected from among the residents older than 20 years old by probability scheme of one out of 2000. Three thousand people were interviewed by questionnaires, and 2,742(91.4%) respondents were used for analysis, and the results are as follows: 1. Ridit(Relatives to an identified distribution it) of category one by sex was 0.26 in man, and 0.25 in woman. Ridit of category two was 0.57 in man and 0.53 in woman, those of category three was 0.72 in man and 0.65 in woman. That of category four was 0.86 in man and 0.85 in woman, that of category five was 0.95 in man and 0.97 in woman, and that of category six was 0.98 in man and 0.99 in woman. The ridits and health related categories by sex were r=.954 in man and r=.966 in woman(p<0.01) 2. Ridits of healthy behavior 2-1. The ridit of males who slept for less than 6 hrs was 0.71, that of those who slept for $7{\sim}8$ hrs was 0.24, and that of those who slept for more than 9 hours was 0.96. The ridit of females who slept for less than 6 was 0.80, that of those who slept for $7{\sim}8$ hrs was 0.32, and that of those who slept for more than 9 hrs was 0.97. 2-2. The ridit of male, who ate breakfast everyday was 0.30, that of those who ate one to four breakfast per week was 0.87, and that of those who never ate breakfasts was 0.96. The ridit of females who ate breakfast everyday was 0.32, that of those who ate breakfast one to four times a week was 0.75, and that of those who never ate breakfast was 0.99. 2-3. The ridit of males whose body weights were 10% lower than normal body weight was 0.45, that of those with $5{\sim}9.9%$ less than normal body weight was 0.28, that of those with ${\pm}4.9%$ of normal body weight was 0.12, that of those whose body weights were $5{\sim}9.9%$ heavier than normal was 0.40, that of those whose body weights were $10{\sim}19.9%$ heavier than normal was 0.74, that of those with $20{\sim}29.9%$ heavier than normal body weights was 0.78 and that of those with 30% heavier than normal body weight was 0.87. That of females with 10% less than normal body weight was 0.53, that of those with $5{\sim}99%$ less than normal body weight was 0.32, that of 4.9% those with ${\pm}f$ normal body weight was 0.14, that of those with 5.0 to 9.9% heavier body weights was 0.43, that of those with 10 to 19.9% heavier body weight was 0.65, that of those with $20{\sim}29.9%$ heavier body weight was 0.94 and that of those with more than 30% of normal body weight was 0.94. 2-4. The ridit of males who exercised everyday was 0.11, that of those who exercised three to four times a week was 0.25, that of those exercising once or twice a week was 0.48, and that of those who never exercised was 0.80. The ridit of females exercising everyday was 0.08, that of those exercising three to four times a week was 0.21, that of those exercising one to two times was 0.35 and that of those who never exercised was 0.72. 2-5. The ridit of males who did not drink at all was 0.14, that of those who drank one or two cups of hard liquor(Soju) was 0.39, that of those who drank a half bottle of Soju was 0.56, that of those who darnk a bottle of Soju was 0.73 and that of those who drank two bottles of Soju was 0.96. The ridit of females who did not drink at all was 0.30, that of those who drank one or two cups of Soju was 0.70, that of those who drank a half bottle of Soju was 0.84, that of those who drank a bottle of Soju was 0.97 and that of those who drank more than two bottles of Soju was 0.99. 2-6 The ridit of males who did not smoke was 0.20, that of those who smoked one or two cigarettes was 0.44, that of those who smoked about ten cigarettes was 0.58, and that of those who smoked more than a pack of cigarettes was 0.85. The ridit of females who did not smoke at all was 0.90, that of those who smokes one or two cigarettes was 0.91, that of those who smoked about the cigarettes was 0.93 and that of those who smoked more than a pack of cigarettes was 0.96 3. The ridit of males who had healthy behavior in six categories was 0.43 and the average age of them was 45, that of those who had healthy behavior in five categories was 0.47 and the average age was 45, that of those who had healthy behavior in three categories was 0.50 and the average age was 43, that of those who had heathy behavior in two categories was 0.60 and the average age was 40, that of those who had healthy behavior in one category was 0.68 and the average age was 38, and that of those who did not have healthy behavior at all in six categories was 0.79 and the average age was 41. The ridit of females who had heathy behavior in six categories was 0.38 and the average age was 45, that of those who had healthy behavior in five categories was 0.40 and the average age was 44, that of those who had healthy behavior in four categories was 0.46 and the average age was 43, that of those who had healthy behavior in three categories was 0.52 and the average age was 44, that of those who had healthy behavior in two categories was 0.57 and the average age was 41, that of those who the healthy behavior in one category was 0.62 and the average age was 40, and that those who did not have healthy behavior in six categories was 0.79 and the average age was 43. 4. The health statues of the persons who the healthy behavior were better than those who did not have healthy behavior. If the people have healthy behavior in young age and they have healthy education continuously, they can live healthier lives.

• Asian Pacific Journal of Cancer Prevention
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• 제15권23호
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• pp.10061-10066
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• 2015

Background: The aetiological relationship between human papillomavirus (HPV) infection and cervical cancer (CC) is widely accepted. Our goal was to determine the prevalence of HPV types in Mexican women attending at the Mexican Institute for Social Security from different areas of Mexico. Materials and Methods: DNAs from 2,956 cervical samples were subjected to HPV genotyping: 1,020 samples with normal cytology, 931 with low-grade squamous intraepithelial lesions (LGSIL), 481 with high grade HGSIL and 524 CC. Results: Overall HPV prevalence was 67.1%. A total of 40 HPV types were found; HPV16 was detected in 39.4% of the HPV-positive samples followed by HPV18 at 7.5%, HPV31 at 7.1%, HPV59 at 4.9%, and HPV58 at 3.2%. HPV16 presented the highest prevalence both in women with altered or normal cytology and HPV 18 presented a minor prevalence as reported worldwide. The prevalence ratio (PR) was calculated for the HPV types. The analysis of PR showed that HPV16 presents the highest association with CC, HPV 31, -33, -45, -52 and -58 also demonstrating a high association. Conclusions: The most prevalent HPV types in cervical cancer samples were -16, -18, -31, but it is important to note that we obtained a minor prevalence of HPV18 as reported worldwide, and that HPV58 and -52 also were genotypes with an important prevalence in CC samples. Determination of HPV genotypes is very important in order to evaluate the impact of vaccine introduction and future cervical cancer prevention strategies.

• 고려인삼학회:학술대회논문집
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• 고려인삼학회 2008년도 춘계 학술대회
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• pp.74-75
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• 2008

This study is for geochemical relationships between ginsengs and soils from three representative soil types from Keumsan, shale, phyllite and granite. For these study, ginsengs, with the field and weathered soils were collected from the three regions, and are analysed for the major and trace elements. In the weathered soils(avg.), the granite and phyllite areas are high in the most of elements while the shale area is low. In the correlation coefficients, negative correlations are shown in the $Al_2O_3$-MgO pair while positive correlations, are shown in the Ba-Sr, Zr, Sr-Zr and Cs-Ge pairs. In the field soils(avg.), the granite and phyllite areas are, generally, high in the most of elements while the shale area is low. In the shale area, the major elements are high in the 4 year soils, but low in the 2 year soils. The LFS(Ba, Sr, Cs) and transitional elements are high in the 2 year soils, but low in the 4 year soils. The HFS(Y, Zr) is high in the 4 year soils. In the correlation coefficients, most of the elements from the 4 year show positive relationships. Positive correlations are shown in the $Al_2O_3$-CaO, MnO-MgO, V-Tl, and Ba-Sr pairs in all localities. In the ginseng contents, clear chemical differences with the ages are shown in the shale and granite ares, but not clear in the phyllite area. In the shale area Mn, Mg, Ba, Sr, and Y contents, increase with ages but decrease in Al, Cs, Be and Cd. In the correlation coefficients, degrees of the correlations for the major elements become low with the ages. Positive correlations are shown in the Al-Mn, Ti, Mn-Ti, Mg-Ca, Ca-K, Ba-Cs, Y and Cs-Y pairs. Comparisons with ginsengs of the same ages from the different areas suggest that generally, the 2 years in the shale and 3 and 4 years in the granite area are distinctive. Relative ratios(granite/ shale area) of the ginsengs are below 1 in the major elements except Mn in the 2 year ginsengs and above 1 in the other elements except Mg and Na in the 4 year. Relative ratios(granite/ phyllite area) of the ginsengs are high in the 3 year from the phyllite area. In the relative ratios(weathered/field soils) of the soils, numbers of the elements showing the ratios of above 1 increase from the shale, to phyllite and granite in the case of the major elements, but decrease in the case of the trace elements. These results suggest that major elements are high in the granite while trace elements are high in the shale area. In the relative ratios between field soils and ginsengs(field soils/ginseng), the shale area, regardless of the ages, show differences of several hundred times in the $Al_2O_3$, $TiO_2$, Y and Tl, of several ten times in the MnO, MgO and Ba and of several times in the CaO contents. These results suggest that ginseng contents are significantly different from the field soils in the $Al_2O_3$, $TiO_2$, Y and Tl, but similar in the CaO contents. The phyllite area, regardless of the ages, show differences of several hundred times in the $Al_2O_3$, $TiO_2$, Y, Tl and Be, of several ten times in the MnO, MgO, $Na_2O$ and Ba, and of several times to ten times in the CaO, $K_2O$ and Sr contents. These results suggest that ginseng contents are significantly different from those of the field soils in the $Al_2O_3$, $TiO_2$, Y, Tl and Be, but similar in the CaO, $K_2O$ and Sr contents. The granite area, regardless of the ages, show differences of several hundred times in the $Al_2O_3$, $TiO_2$, Tl and Be, of several ten times in the Ba, and of several times to ten times in the MgO and CaO contents. Of the other elements, differences of several times to ten times are shown in the MnO, $K_2O$ and Sr contents. These results suggest that ginseng contents are significantly different from those of the field soils in the $Al_2O_3$, $TiO_2$, Tl and Be, but similar in the $K_2O$ and Sr contents. Comparisons among the different ages from the same area suggest that, in the case of shale area, differences of several hundred times in the $Al_2O_3$ and $TiO_2$, of the several ten times in the MnO, MgO and Ba and several times in the CaO and $K_2O$ are shown in the 2 year ginsengs. Differences of several hundred times in the $Al_2O_3$, $TiO_2$, Cs, Y, Tl and Be, of above several ten times in the MnO, MgO, $K_2O$ and Ba, and of several times in the CaO and Sr are shown in the 3 year ginsengs. Differences of several hundred to thousand times in the $Al_2O_3$, of above several hundred times in the $TiO_2$, Cs and Y, and of several ten times in the MnO, MgO, $K_2O$ and Ba, and of several times in the $Na_2O$ are shown in the 4 year ginsengs. These relationships suggest that, regardless of the localities in the shale area, $Al_2O_3$ contents of the soils show big differences from those of the ginsengs. Regardless of the ages of ginsengs, comparisons with the overall average contents of each area show differences of several hundred times in the $Al_2O_3$, $TiO_2$, Cs and Tl and of several ten times in the MnO. These overall relationships suggest that the $Al_2O_3$, $TiO_2$, Cs and Tl contents of the soils are higher than those of the ginsengs, show big differences between two and low different contents are found in the MnO. In detail, differences of several hundred times in the Y, and ten times in the MgO and Sr, and of several times in the CaO, $Na_2O$, $K_2O$ in the case of shale area, are shown. These results suggest that the soils are higher than the ginsengs in the Y and significantly differences in Y, and moderately differences in the MgO and Sr, and low differences in the CaO, $Na_2O$ and $K_2O$ are shown between soils and ginsengs.

• 대한핵의학회지
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• 제34권5호
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• pp.418-425
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• 2000

목적: 감마카메라를 이용한 사구체 여과율 측정에 필요한 신장 깊이에 관한 자료는 대부분 Tonnesen 등이 서양인의 신장 깊이를 토대로 작성한 방정식을 채용하고 있는데 이 방법은 신장 깊이를 과소 평가하는 것으로 알려져 있다. 이에 저자들은 서양인과 체격 조건이 다른 한국인의 신장 깊이에 관한 방정식을 도출하여 다른 방법과 비교하고 이를 사구체 여과율 측정에 이용하고자 하였다. 대상 및 방법: 신장에 이상 소견이 없는 성인 300명(남:여=167:133, 평균나이, 50.9세)의 복부 CT 사진 중 신문이 나온 영상에서 피부면으로부터 신장의 최전면과 최후면까지의 깊이를 각각 측정하여 평균 깊이를 구하였다. 대상이 된 300명중 200명을 무작위 추출하여 성별, 나이, 체중, 키를 변수로 하여 방정식을 도출하였고, 이를 토대로 산출한 신장 길이와 대조군 100명의 신장 길이 측정치를 비교하였다. 이어 Tc-99m DTPA 신장 신티그람을 시행한 또 다른 48명(남:여=25:23, 평균나이: 50.6세)에서 Tonnesen, Taylor와 저자들의 방정식으로 각각 산출한 신장 깊이를 사용하여 Gates 방법으로 사구체 여과율을 측정하여 비교 분석하였다. 결과: CT로 측정한 신장 깊이의 평균은 남자 우신; 6.9 좌신; 6.7, 여자 우신: 6.7 좌신: 6.6 cm이었다. 저자들의 측정치와 비교할 때 Tonnesen 방정식으로 구한 산출기(남자 우신: 5.5 좌신: 5.5, 여자 우신: 5.4 좌신: 5.4 cm)는 낮았고 그 차이는 통계적으로 유의하였다. Taylor 방정식의 산출치(남자 우신: 6.8 좌신: 6.4, 여자 우신: 6.6 좌신: 6.1 cm)는 여자 좌신을 제외하고는 모두 비슷하였다. 저자들이 도출한 방정식은 남자 우신: 12.813(체중/키)+0.002(나이)+2.264, 좌신: 15.344(체중/키) +0.011(나이) +0.557, 여자 우신: 12.936(체중/키)+0.014(나이)+1.462 좌신: 13.488(체중/키)+0.019(나이)+0.762 이었다. 이 방정식의 산출치를 대조군의 측정치와 비교한 결과 남자 우신과 좌신, 여자 우신과 좌신에서의 상관계수 r은 각각 0.529, 0.729, 0.601, 0.724 이었다. 3가지 방정식을 이용하여 측정한 사구체 여과율 중 저자들의 방정식으로 구한 것이 가장 큰 값을 보여 정상 사구체 여과율에 가장 가까웠고 Tonnesen 방정식으로 구한 것이 가장 낮았다. 결론: 한국인 신장 깊이를 토대로 만든 방정식을 이용하여 한국인의 사구체 여과율을 비롯한 신장 청소율과 Tc-99m DMSA 신장 섭취율 등을 보다 정확하게 측정할 수 있을 것으로 기대된다.

• Asia Marketing Journal
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• 제14권1호
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• pp.1-24
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• 2012

본 연구는 고객만족과 기업가치 성과간의 관계를 분석하는 것이 목적이다. 기업가치성과는 주가와 신용등급으로 나눌 수 있는데, 전자는 기업의 시장가치이고 후자는 자금조달비용이라 구분하여 사용되고 있다. 고객만족과 주가와의 관계는 비교적 오래전부터 연구되어 왔으나 신용등급과의 관계는 최근 들어 연구되기 시작하였다. 대표적으로 Anderson and Mansi(2009)의 연구에서는 양자가 긍정적으로 관련된 것으로 밝혀졌으나, 윤상운(2010)이 국내자료를 사용한 연구에서는 그 관계가 입증되지 못하였다. 일치하지 않는 두 연구의 결과에서 아이디어를 얻어 본 연구에서는 고객만족이 신용등급에 긍정적 영향을 미치는 것으로 보고 이를 검증하였다. 두 연구에서 사용한 모델을 참고로 하였고 특히 우리나라 실정에서는 정부지원이 중요한 변수임을 감안하여 이를 포함한 연구모형을 설정하여 검증한 결과 긍정적 관련성이 있는 것으로 나타났다. 추가분석에서 자산규모가 큰 기업보다 작은 기업에서, 제조업보다 서비스업에서 고객만족이 신용등급에 더 유의한 긍정적 영향을 미치는 것으로 나타났다.

• Asia Marketing Journal
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• 제12권4호
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• pp.55-78
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• 2011

외식업계에서는 충성도제고를 위한 장기적 고객 관리 프로그램으로서 사용금액 대비 일정률의 포인트를 적립해주는 고객보상(로열티)프로그램을 시행해왔으며, 단기적인 매출 증대를 목적으로 신용카드사나 이동통신사와의 전략적 제휴를 통해 소비자에게 할인혜택을 제공하는 제휴할인카드를 경쟁적으로 도입하고 있다. 포인트 적립과 제휴카드할인 프로그램은 추구하는 목적은 서로 다르나 소비자에게는 동일한 구매시점에 둘 중에서 하나를 선택해야하는 경합적인 대안이 된다. 일반적으로 소비자는 손실에 대해 더 민감하게 반응하는 위험회피 성향을 보이며, 실용적 동기에 의한 취득 및 거래효용의 관점에서 할인이 강력한 구매 동기가 되므로, 분리된 이익으로서의 포인트 적립 보다 할인 혜택을 제공함으로써 손실의 감소로 인식되는 제휴카드할인이 더 선호될 것으로 예상할 수 있다. 기업의 입장에서도 제휴기업간의 비용분담을 통해 보다 적은 비용으로 큰 소비자 할인혜택을 제공할 수 있다는 비용효율의 장점 및 경쟁 대응 필요성 때문에 제휴카드할인을 도입하게 된다. 그러나 할인판촉은 실제적인 비용이 투입되므로 매출의 증가를 통해 비용 보다 큰 수익이 보장될 때만 의미를 가지는 촉진 수단이다. 외식업의 경우 방문객수가 증가해야 매출의 증대를 이룰 수 있으며 운영효율이 향상된다. 테이블당 고객수 증가는 공간효율을 높여주어 이익개선에 기여가 크다. 따라서 제휴카드할인이 실제적인 기업성과향상을 가져오려면 할인이 객수의 증가 특히 테이블당 객수의 증가에 기여를 해야 한다. 제휴카드할인이 객수증가 및 이익률의 향상에 도움이 되는지의 여부를 알아보기 위하여 패밀리 레스토랑업체의 실제 매출 데이터를 사용하여 검증해 본 결과 포인트 적립제도는 객수 증가와 유의적 관계를 보이지 않은 반면 제휴할인은 객수 증가에 실제적인 영향이 있음이 밝혀졌으며, 할인율이 증가하면 테이블당 고객수도 증가하며 약 25%의 할인이 제공되면 추가로 한 명의 고객이 유인되는 효과가 있었다. 또한 수익성의 측면에서는 1인당 지불금액 즉 객단가는 할인율의 증가에 따라 하락하는 경향을 보였지만 객수의 증가로 인한 추가이익이 추가비용을 상쇄하고 있어서 제휴할인카드의 도입이 비용 대비 효과의 측면에서 적극적으로 고려할 수 있는 촉진 수단임이 입증되었다. 본 연구는 기업의 실측 데이터를 활용하고 있다는 점에서 소비자 태도나 의도의 변화를 기준으로 기업의 의사 결정 정보를 제공하고자한 기존연구보다 현실적인 접근을 하고 있다. 즉, 기업의 실제 데이터로 제휴카드할인 프로그램의 효과를 측정하였고, 포인트 적립 및 차감제도를 직접 비교함으로써 기업에게 향후 마케팅 전략 수립에 관한 현실적인 시사점을 제공하였다는 점에서 연구의 의의를 찾을 수 있을 것이다.

• 마케팅과학연구
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• 제18권1호
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• pp.115-139
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• 2008

IMF이후 경쟁의 심화와 적대적인 경영환경에 효과적으로 대응하고자 많은 호텔기업들이 구조조정을 실시해오고 있다. 이러한 구조조정은 인력감축을 동반하기 때문에 구조조정 과정에서 공정성을 지각하는데, 인력감축에서 살아남은 생존자들이 인력감축의 절차나 실무에서 불공정성을 지각할 때 상사에 대한 신뢰감이나 조직유효성을 감소시키는 것으로 나타났다. 따라서 본 연구는 호텔기업을 대상으로 구조조정 이후 살아남은 생존자를 대상으로 정리해고의 공정성 지각이 경영진의 신뢰, 직무만족 및 조직몰입에 어떠한 영향을 미치는지를 살펴보고자 하는 것이다. 이러한 연구목적을 달성하기 위해 실증분석을 실시한 결과 잔류종업원들은 구조조정 과정에서 절차 공정성 및 분배 공정성을 높게 지각 할수록 경영진에 대한 신뢰감과 조직 몰입이 높아지는 것으로 나타났다. 그러나 구조조정 과정에서 절차 공정성을 높게 지각할수록 직무만족은 높아지는 것으로 나타났지만, 분배 공정성은 직무만족과는 인과관계가 없는 것으로 나타났다. 또한 구조조정 과정에서의 경영진에 대한 신뢰감이 높아질수록 직무만족이나 조직몰입은 높아지는 것으로 나타났다.

• 한국식품조리과학회지
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• 제8권4호
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• pp.387-396
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• 1992

This study was conducted to examine the favorable taste of food color for one month of November 1991 With 200 college students consisting 100 male and 100 female students. The color to examine the favorable food was based on Munsell color standard of ten colors such as F. Birren seven colors (red, orange, yellow, yellowish green, green, blue and violet), brown, pink and black. And then, the data of this study was analysed by using frequency(%), mean values, standard deviation, t-test, Chi-square, Spearman correction with SAS Package on the basis of 100% collection and reliable coefficient alpha= .775. The result of this study is summarized as follows. 1. It was shown that the male college students (59%) showed remarkable interest in the food color higher than that of female college students (92%), and that 85% of male students and 97% of female students considered that the food color has an effect on appetite. In addition, the food name having an effect of the food color on appetite appeared in such order as carrot (13.0%), apple (10.9%), spinach (7.0%), cucumber (6.0%) and red pepper (5.6%). The important factor in choosing the favorable food was the taste for both male and female college students, while the male and female students considered the food color as the 4th, respectively, and the 3rd important factor in choosing the favorable food. 2. The favorable food color appeared in order such as orange, red, yellow, yellowish green, green, blue, violet, pink, black and brown colors for the male college students, and in order such as red, orange, yellow, green, yellowish green, brown, violet, black, pink and blue. Also, there was difference between the male and female college students in such colors as brown, yellowish green, blue and pink. It was also shown that there was no relation between the male and female college students in examining the order of favorable food colors and general colors when selecting null hypothesis (ASE: .405). The food name associated with the color was apple for red color, orange for orange color, coffee for brown color, banana for yellow color, lettuce for yellowish green color, spinach for green color, mackerel for blue color, eggplant for violet color, sausage for pink color and bean for black color 3. The favorable color combination of both male and female college students showed red with green, orange with yellow, yellow with green, green with yellow, pink with violet and black with black. In addition, the favorable combination of the male college students indicated brown with black, yellowish green with orange, blue with red and violet with yellow while the female college students did brown with yellow, yellowish green with green, blue with yellow and violet with pink. The favorable combination color showing difference between the male and female college students included orange, brown, violet, pink and black colors. 4. The relation between the food color and terms of favorable taste showed that “light and mild color” is yellow, that “untasty color” is black, that “sourish and puckery color” is orange, that “bitter color” is violet, that “hot color” is red, and that “fresh color” is green which were answered by both male and female college students. However, the male and female college students considered yellow, respectively, and orange as “tasty color”, and black and yellow, respectively, as “sweet color”. Then, the taste term showing difference between male and female college students included “light”, “mild”, “sourish”, “tasty” and “sweet”. Based on the above result of this study, it is apparent that there is a close relation between the food color and appetite while being difference between the general color and taste. In addition to this fact, there is also some differences between male and female college students in the taste of food color.

• 한국수산과학회지
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• 제34권1호
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• pp.57-69
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• 2001

한반도 남해 내만역에서 계절별로 4회에 걸친 입자유기물질 농도분포를 조사한 결과 입자유기물질은 대체로 봄철과 여름철 농도가 가을과 겨울철에 비해 비교적 높다는 것을 나타내었다. 입자유기물질 농도가 높은 봄과 여름철 C : Chl a나 C . N비는 해양의 식물플랑크톤의 전형적인 비값들을 나타내고 Chl a농도 역시 이기간 중에 높게 나타나 이들 내만역에서 입자유기물질 계절 변동은 식물플랑크톤 생물량과 밀접한 상관을 갖는다는 것을 보였다. 조사 해역별 입자유기물질 성분의 농도 분포는 진해만에서 고성만과 강진만에 비해서 높은 농도를 나타내었는데, 다른 해역에 비해서 진해만에서 높은 Chl a: PPr-N비 값들은 진해만이 다른 내만역들 보다 더욱 부영양화 되었다는 것을 나타내어 부영양화 수준에 따른 식물플랑크톤 생산력이 각 내만역 사이 입자유기물질 농도의 공간적 차이를 결정하는 중요한 요인이라는 것을 시사했다. 각 내만역 내에서 입자유기물질 수평농도 분포는 소규모 내만역내에서도 공간적으로 큰 농도차를 보일 수 친다는 것을 나타내었는데, 대도시에 인접한 수역에서 높은 입자유기물질 농도와 높은 식물플랑크톤 기여는 이들 도시로부터 다량의 영양염 유입을 시사하였고, 양식장이 밀집한 수역에서 상대적으로 낮은 입자유기 물질 농도는 양식생물의 높은 섭이활동을 반영하는 것으로 고려되었다. 식물플랑크톤 성장 제한 영양염은 계절별로 각 내만역내에서 입자유기물질 C : N : P 원소 변동비로부터 평가되었는데, 진해만과 고성만에서 Redfield비와 일치하는 C : N 변동비 (6.6)는 이 해역의 입자유기물질이 식물플랑크톤에서 유래하고 있다는 것을 나타내었던 반면, 강진만에서는 5.0의 다소 낮은 C : N비를 보였다. 진해만과 고성만에서 여름철 18.2와 24.6의 높은 N : P 변동비는 인산염이 이 해역들의 식물플랑크톤 성장을 제한할 수 있는 것으로 나타나지만 봄철 10.8과 14.7의 낮은 비값은 오히려 질소계 영양염에 의한 제한을 시사한 반면, 강진만에서 N : P 변동비는 $6.3\~12.8$로 조사기간 모두 질소계 영양염이 제한 영양염으로 작용한다는 것을 시사하였다.