신뢰대상의 다차원적 접근법에 의한 신뢰와 재구매 의도와의 관계 (The Relationship between Trust, Trustworthiness, and Repeat Purchase Intentions: A Multidimensional Approach)
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- 마케팅과학연구
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- 제18권1호
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- pp.1-31
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- 2008
신뢰는 인간관계에서 동서고금을 통해 언제나 주목을 받아온 주제였으며, 신뢰의 중요성은 경영학 분야는 물론 인간생활의 모든 분야에서 이미 오랜 전부터 인식되어 왔다. 그러나 대부분의 연구는 주로 개인 간의 신뢰인 종업원에 대한 신뢰에만 집중하는 단일 차원적 관점에서 연구되어 왔다. 본 연구는 이와 같이 지금까지 주로 단일차원으로 연구되어 온 신뢰 대상을 판매원, 제품/서비스, 그리고 기업의 3차원으로 다차원화하여 이들 신뢰 대상이 재구매 의도에 미치는 영향을 검증하였다. 서울, 대구 경북지역의 거주자로 백화점에서 구매 경험이 있는 남녀 고객을 대상으로 수집된 자료를 분석한 결과, 기존 연구들에서 주로 다루어진 판매원신뢰뿐만 아니라 기업신뢰와 제품/서비스신뢰 또한 고객신뢰의 중요한 대상으로 나타나, 신뢰 대상은 다차원적인 구성개념임이 밝혀졌다. 이들 3차원의 신뢰는 모두 재구매 의도에 유의한 영향을 미치는 것으로 나타났으며, 특히 기업신뢰가 판매원신뢰와 제품/서비스신뢰보다 재구매 의도에 더 영향을 미치는 것으로 나타났다. 판매원신뢰와 제품/서비스신뢰의 영향요인으로 역량과 선의를, 기업신뢰의 영향요인으로 기업 평판과 물리적 환경을 설정하여 검증한 결과 역량과 선의는 판매원신뢰와 제품/서비스신뢰 모두에 유의한 영향을 미치는 것으로 나타났다. 기업신뢰의 경우, 평판은 유의한 영향을 미치는 것으로 나타났으나, 물리적환경은 유의한 영향을 미치지 않은 것으로 나타났다.
연구 목적 본 연구의 목적은 그린 기술의 채택 현상을 디지털 지식의 제공 여부로 이해하는 것이다. UTAUT2를 이론적 기반으로 하되 디지털 옵션 이론과 결합하였다. 특히 일반적인 UTAUT2 관련 연구들이 IT자체에 대한 수용 현상을 설명하기 위해 사용된 것과는 달리 본 연구에서는 IT의 산물인 디지털지식이 그린 기술이라는 대상을 채택하는데 긍정적인 영향을 주는지에 대해서 초점을 두었다. 연구설계/방법론/접근법 UTAUT2를 근거로 하되 그린 기술의 채택 현상을 설명하는데 유용한 요인들을 파악하기 위하여 내용분석을 실시하였다. 그 결과로 본 연구에서는 그린기술을 위한 수정된 UTAUT2 모형을 개발하였으며 그에 맞는 36개의 설문 문항을 개발하였다. 각 문항의 측정은 리커트 7점 척도를 채택하였다. 한 기관의 패널 자료로부터 총402명의 유효한 설문을 획득하였다. 사전 검증을 마치고 획득한 설문결과를 PLS 2.0M3와 SPSS 20.0을 이용하여 분석하였으며 가설검증을 위해 구조방정식 분석을 수행하였다. 결과 통계분석 결과 개발된 UTAUT2 수정 모형은 수요자들의 그린기술 채택 현상을 적절히 설명하는 것으로 실증분석 결과 나타났다. 사회적 영향은 전통적인 UTAUT나 UTAUT2에서 사용하는 효용가치나 쾌락가치보다 그린기술의 채택하는 맥락 하에서의 수용 행위를 더 잘 설명하고 있었다. 또한 디지털 지식과 그린기술의 채택, 즉 환경 친화적 제품에 대한 태도에 영향을 주는 요인들 사이의 인과관계는 유의한 것으로 판정되었다. 아울러 디지털 지식은 어떤 잠재적 사용자들이 그린기술을 잘 활용하고 있는 그들의 동료들로부터 학습하기 위해서 유용한 매체인 것으로 밝혀졌다.
The purpose of this study was to identify risk factors related to sexual function of women with coronary artery disease, and to determine the predictors of sexual function. The study design, a descriptive correlational study, was done through structural questionnaire and interview. A total of 50 subjects from C University Hospital at Kwang-ju city who have undergone coronary angiography at department of cardiology were observed and interviewed from Feb. 22, 1999 to March. 23, 1999. The number of affected vessels, the level of total serum cholesterol, and the ejection fraction of 2-D echo cardiography were analyzed to evaluate the severity of coronary artery disease. And also type A behavior pattern, health behavior, Brief Index of Sexual Functioning for Women (BISF-W) were measured. The data obtained were analyzed using percentage, mean and standard deviation, t-test, ANOVA, Pearson's correlation coefficient, and stepwise multiple regression analysis via SPSS PC+. The results of this study were as follows: 1. The mean age of the subjects were 58.1 and 72.0% of those have been married over 30 years. Seventy two percentage were unemployed and monthly family income of 56.6% was less than 1,000,000 won (approximately $ 840). Eighty percent were in their postmenopausal state, and the frequency of sexual intercourse of 84.0% were two to three times per month. 2. The scores of type A behavior pattern were from 16 to 38(mean 24.94) and health behavior ranged from 21 to 43(mean 31.2). Abstinence from smoking, alcohol, and caffeine were best compliant factors and weight control and exercise were least abided ones. The result of 2D-ECHO EF showed that the half of the subjects were abnormal, and 24% had more than 240mg/dl of total serum cholesterol. The coronary angiography showed that 64% of the subjects had more than one affected vessels. 3. The predictors to explain the factor score of 'orgasm' were number of health examination, the pre- or post-menopausal state, protestant, number of coronary vessel affected, level of serum total cholesterol, and comorbid group of hypertension and diabetes, and it's total variance accounted for 52.4%. The predictors to explain the factor score of 'sexual activity' were comorbid group of hypertension and diabetes and type A behavior pattern, which accounted for 22.4% of total variance. The predictors to explain the factor score of 'sexual satisfaction' were type A behavior pattern, no religion, exercise, level of serum total cholesterol, and pre or post menopausal state, which accounted for 52.1%. The predictors to explain the factor score of 'sexual desire' were the period of marriage, type A behavior, employment or unemployment, and weight control, which accounted for 43.2%. The predictors to explain the factor score of 'external force of sexual functioning' were physical overload and exercise, which accounted for 41.1%. The predictors to explain the factor score of 'sexual activity' were family monthly income, catholics, and exercise, and which accounted for 35.4%. Above results lead us to some consensus that sexual function of women with coronary artery disease is related to various factors including vasogenic factors such as total serum cholesterol level, number of coronary vessel affected, an endocrinal factor such as menopausal state, and type A behavior pattern as a sociopshychological factor. And also health behaviors such as fitness care, overwork, weight control, and emotional tension are contributed to sexual function.
The objective of this study was to analyze the in vitro and in vivo corrosion products of low and high copper amalgams. The four different types of amalgam alloy used in this study were Fine cut, Caulk spherical, Dispersalloy, and Tytin. After each amalgam alloy and Hg were triturated according to the directions of the manufacturer by means of the mechanical amalgamator(Amalgam mixer. Shinhung Co. Korea), the triturated mass was inserted into a cylindrical metal mold which was 12mm in diameter and 10mm in height. The mass was condensed by 150Kg/cm compressive force. The specimen was removed from the mold and aged at room temperature for about seven days. The standard surface preparation was routinely carried out by emery paper polishing under running water. In vitro amalgam specimens were potentiostatically polarized ten times in a normal saline solution at
Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70