6 research outputs found

    A Review of Marketing Literature on Market Responses to Product Harm Crises

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    λ³Έ λ…Όλ¬Έμ—μ„œλŠ” μ œν’ˆ 결함 μœ„κΈ° λ°œμƒμ— λ”°λ₯Έ μ‹œμž₯ λ°˜μ‘ 츑면을 λ§ˆμΌ€νŒ… λ¬Έν—Œμ„ μ€‘μ‹¬μœΌλ‘œ μ‚΄νŽ΄λ³΄κ³ , μ†ŒλΉ„μžμ˜ 심리적 처리 기제λ₯Ό λΆ„μ„ν•œ μ‹€ν—˜ 연ꡬ 및 μ†ŒλΉ„μžμ˜ μ‹€μ œ ꡬ맀 행동을 λΆ„μ„ν•œ κ³„λŸ‰ 연ꡬλ₯Ό λ‹€μ–‘ν•˜κ²Œ μ‚΄νŽ΄λ³΄μ•˜λ‹€. μ†ŒλΉ„μžμ˜ 인ꡬ톡계적 νŠΉμ„±μ— 따라 그리고 μ†ŒλΉ„μžμ˜ 사전 κΈ°λŒ€μ— 따라 μ œν’ˆ 결함 μœ„κΈ°μ— λŒ€ν•œ λ°˜μ‘μ΄ λ‹€λ₯΄λ‹€. λ˜ν•œ μ œν’ˆ 결함 μœ„κΈ°μ˜ 원인을 μ§„λ‹¨ν•˜λŠ” μ†ŒλΉ„μžμ˜ 심리적 처리 기제의 차이에 따라 λ°˜μ‘μ΄ 상이함을 μ—¬λŸ¬ μ—°κ΅¬μ—μ„œ μ œμ‹œν•˜κ³  μžˆμŒμ„ μ‚΄νŽ΄λ³΄μ•˜λ‹€. μ œν’ˆ 결함 μœ„κΈ°κ°€ κΈ°μ—…μ˜ κ΄‘κ³  ν™œλ™μ˜ 효과, μ†ŒλΉ„μžμ˜ 가격 민감도 λ“± λ§ˆμΌ€νŒ… ν™œλ™μ˜ νš¨κ³Όμ— μ–΄λ– ν•œ 영ν–₯을 λ―ΈμΉ˜λŠ”μ§€μ— λŒ€ν•œ 연ꡬ도 μ‚΄νŽ΄λ³΄μ•˜λ‹€. 기쑴의 λ§ˆμΌ€νŒ… 연ꡬ λ¬Έν—Œλ“€μ΄ 깊이 λ°νžˆμ§€ λͺ»ν•œ λ‹€μŒκ³Ό 같은 λΆ„μ•Όλ₯Ό μΆ”ν›„ 연ꡬ가 더 이루어져야 ν•  λ°©ν–₯으둜 μ œμ‹œν•œλ‹€. λ¨Όμ €, μ†ŒλΉ„μžμ˜ λ‹€μ–‘ν•œ νŠΉμ„±μ— λ”°λ₯Έ λ°˜μ‘ μ΄μ§ˆμ„±μ— λŒ€ν•œ 연ꡬ가 ν•„μš”ν•˜λ‹€. λ‘˜μ§Έ, μ œν’ˆ 결함 μœ„κΈ° λ°œμƒ ν›„ μ‹ λ’° 회볡과 κ΄€λ ¨λœ ν”„λ‘œμ„ΈμŠ€μ— λŒ€ν•œ μ†ŒλΉ„μžμ˜ λ―Έμ‹œμ  행동 μΈ‘λ©΄μ—μ„œ μ–΄λ–€ 과정을 거쳐 μ†ŒλΉ„μžλ“€μ΄ 결함이 λ°œμƒν•œ λΈŒλžœλ“œμ— λŒ€ν•΄ μ‹ λ’°λ₯Ό νšŒλ³΅ν•˜λŠ”μ§€, ν˜Ήμ€ μ–΄λ–€ μ‘°κ±΄μ—μ„œ μ‹ λ’°κ°€ νšŒλ³΅λ˜λŠ”μ§€μ— λŒ€ν•œ 연ꡬ가 μ΄λ£¨μ–΄μ§ˆ ν•„μš”κ°€ μžˆλ‹€. μ…‹μ§Έ, μ œν’ˆ 결함 μœ„κΈ°μ— 따라 μ†ŒλΉ„μžλ“€μ˜ μ œν’ˆ κ΄€λ ¨ νƒœλ„μ™€ 행동이 μœ„κΈ° λ°œμƒ μ „ μˆ˜μ€€μœΌλ‘œ νšŒλ³΅λ˜κΈ°κΉŒμ§€ κ±Έλ¦¬λŠ” μ‹œκ°„μ„ μ œν’ˆ μœ ν˜•λ³„, μ†ŒλΉ„μž μœ ν˜•λ³„, μ œν’ˆ-μ†ŒλΉ„μž 관계 μœ ν˜•λ³„ λ“±μœΌλ‘œ κ΅¬λΆ„ν•˜μ—¬ μ’€ 더 깊이 이해할 ν•„μš”κ°€ μžˆλ‹€. λ§ˆμ§€λ§‰μœΌλ‘œ, 광고와 λ”λΆˆμ–΄ μ΄‰μ§„μ˜ μΈ‘λ©΄μ—μ„œ μ–΄λ–€ 촉진 ν™œλ™μ΄ μœ νš¨ν•œμ§€ μ–΄λ– ν•œ 맀체λ₯Ό ν†΅ν•œ 촉진 ν™œλ™μ΄ μˆ˜μš©μ„±μ΄ 높은지 λ“±μ˜ 연ꡬ가 ν•„μš”ν•˜λ‹€κ³  νŒλ‹¨λœλ‹€.This paper reviews marketing literature on market response to product harm crises, including both experimental studies on consumers psychological responses and quantitative studies on consumers purchase behaviors. According to the literature, consumer responses to product harm crises vary across gender and age. And it has been shown in the literature that the differences in consumer attribution mechanism also result in heterogeneous responses to crises. Marketing researchers have also investigated the effectiveness of marketing activities such as advertising and price discount during product harm crises. Based on the review, this paper suggest a few directions for future research as follows. First, more studies can be done on the effect of consumer characteristics other than age and gender. Second, it would be interesting to investigate microprocesses that underlies the restoration of consumer confidence after product harm crises. Third, the duration of product harm crises can be studied with a more rigorous approach. Finally, the impacts of various promotional activities have been understudied. Researchers can study further on the type of effective promotion, the type of effective medium, or the role of promotion during product harm crises.λ³Έ μ—°κ΅¬λŠ” μ„œμšΈλŒ€ν•™κ΅ κ²½μ˜μ—°κ΅¬μ†Œμ˜ 연ꡬ비 지원을 λ°›μ•„ μˆ˜ν–‰λ˜μ—ˆλ‹€

    Predictive Modeling of Customers Insurance Purchase Behaviors

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    λ³Έ 논문은 μ‹€μ œ μ‹€λ¬΄μž(practitioner)에 μ˜ν•΄μ„œ, 그리고 학계 ν˜Ήμ€ μ—°κ΅¬μž(academics)에 μ˜ν•΄μ„œ 제일 많이 μ“°μ΄λŠ” 쑰직문화 츑정도ꡬ가 무엇이고, κ·Έκ²ƒμ˜ ꡬ체적 ν™œμš©λ°©λ²•μ€ 무엇인지 νŒŒμ•…Β·μ „λ‹¬ν•˜λŠ” 데 λͺ©μ μ΄ μžˆλ‹€.The purpose of this paper is to let readers know which measurement tools of organizational culture are most widely used by both practitioners and academics around the world. The two most widely used measurement tools are Kilmann-Saxton Culture Gap Survey and Quinn & Camerons Competing Values Framework. A detailed descriptions of what the tools are and how they are used in practice are provided so that they can readily be used by Korean readers. In the case of Competing Values Framework, in addition to the widely-known-andused Organizational Culture Assessment, both Leadership Style Assessment and Leadership Competency Assessment are described also.λ³Έ μ—°κ΅¬λŠ” μ„œμšΈλŒ€ν•™κ΅ κ²½μ˜μ—°κ΅¬μ†Œμ˜ 연ꡬ비 지원을 λ°›μ•„ μˆ˜ν–‰λ˜μ—ˆλ‹€

    μ½”λ‘œλ‚˜19의 μž…μ›κΈ°κ°„: κ΅­λ‚΄ κ°œμΈμˆ˜μ€€ 연ꡬ

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    ν•™μœ„λ…Όλ¬Έ (석사) -- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : λ³΄κ±΄λŒ€ν•™μ› 보건학과(보건학전곡), 2021. 2. κΉ€ν˜Έ.Background: Since the first case of a novel coronavirus 2019(COVID-19) was reported in January 20th 2020, COVID-19 in South Korea has continuously. As a result, the lack of medical resources, especially the hospital beds, has become a serious problem. Therefore, this study aims to contribute to an efficient distribution of medical resources by identifying variables related to hospitalization, admission to intensive care units, and death of patients with COVID-19 using a nationwide individual-level COVID-19 data provided by the Korea Center for Disease Control and Prevention. Methods: This study uses individual-level COVID-19 clinical data to assess the risk factors' association with hospitalization, admission to intense care units, and death. The generalized linear model with gamma distribution was performed. Results: Distribution of the hospitalization of patients with COVID-19 was right skewed and followed gamma distribution. The mean hospitalization of patients with COVID-19 was 25.75 days. The age of the patients was significantly associated with the hospitalization(25.3(95% CI: 24.6, 26) days for age 0-39, 27(95% CI: 26.2, 27.7) days for age 40-59, 28.3(95% CI: 27.6, 29.2) days for age 60-79, and 26.5(95% CI: 25.1, 27.9) days for age>80), admission to ICU(RR=2.0(95% CI: 1.0, 3.7) for age 40-59, 7.4(95% CI: 4.1, 13.4) for age 60-79, and 11.0(95% CI: 5.4, 22.3) for age>80, compared to age 0-39), and death(RR= 5.9(95% CI: 3.4, 10.3) for age 60-79, 58.6(95% CI: 32.3, 106.3) for age>80, compared to age 40-59). Also, clinical symptoms on admission, including cough(27.6(95% CI: 25.2, 26.6) days; compared to 25.9), myalgia(27.3(95% CI: 26.5, 28.2) days; compared to 26.2), and vomiting(27.2(95% CI: 26.3, 28.3) days; compared to 26.3) were significantly associated with longer hospitalization. However, association between underlying disease or past history of the patient with hospitalization were not significant. Also, males were at higher risk for admission to ICU(RR=2.6(95% CI: 1.9, 3.6)) and death(RR=2.3(95% CI: 1.6, 3.1)) than females. Also, underlying disease or past history including diabetes(RR=2.2(95% CI: 1.6, 3.1)), chronic kidney disease(2.4(95% CI: 1.1, 5.1)), and cancer(2.4(95% CI: 1.3, 4.4)) were significantly related to a death. Conclusion: This study found several demographic and clinical characteristics associated with the duration of hospitalization, usage of the intensive care units, and mortality. These findings can provide evidence to distribute medical resources more efficiently.연ꡬ배경: 2020λ…„ 1μ›” 첫 ν™•μ§„μž 이후, λŒ€ν•œλ―Όκ΅­μ˜ μ½”λ‘œλ‚˜19 μœ ν–‰μ€ λŠμ΄μ§€ μ•Šκ³  μžˆλ‹€. 이둜 인해 병상 λ“± ν•œμ •λœ μ˜λ£Œμžμ›μ˜ 뢀쑱이 μ‹¬κ°ν•œ 문제둜 λŒ€λ‘λ˜κ³  μžˆλ‹€. 이에 λ³Έ μ—°κ΅¬λŠ” μ§ˆλ³‘κ΄€λ¦¬λ³ΈλΆ€κ°€ μ œκ³΅ν•˜λŠ” μ „κ΅­λ‹¨μœ„ κ°œμΈμˆ˜μ€€ μž„μƒμžλ£ŒμΈ μ½”λ‘œλ‚˜19 ν™•μ§„μž μž„μƒμ—­ν•™μ •λ³΄λ₯Ό μ΄μš©ν•˜μ—¬ μ½”λ‘œλ‚˜19 ν™•μ§„μžμ˜ μž…μ›κΈ°κ°„ 및 μ€‘ν™˜μžμ‹€ μ‚¬μš©, 사망여뢀 λ“±κ³Ό 상관이 μžˆλŠ” λ³€μˆ˜λ₯Ό νŒŒμ•…ν•¨μœΌλ‘œμ„œ 보닀 효율적인 μ˜λ£Œμžμ› 뢄배에 κΈ°μ—¬ν•˜κ³ μž ν•œλ‹€. 연ꡬ방법: λ³Έ μ—°κ΅¬λŠ” μ½”λ‘œλ‚˜19 ν™•μ§„μž μž„μƒμ—­ν•™μ •λ³΄λ₯Ό μ΄μš©ν•˜μ—¬ μ½”λ‘œλ‚˜19 ν™•μ§„μžκ°€ λ³΄μœ ν•œ μœ„ν—˜μš”μΈλ“€κ³Ό μž…μ›κΈ°κ°„, μ€‘ν™˜μžμ‹€ μ‚¬μš©μ—¬λΆ€, 그리고 μ‚¬λ§μ—¬λΆ€μ˜ 관계λ₯Ό ν™•μΈν–ˆλ‹€. 이λ₯Ό μœ„ν•΄μ„œ 감마 뢄포 μΌλ°˜ν™” μ„ ν˜•λͺ¨ν˜•μ„ μ‚¬μš©ν•˜μ˜€λ‹€. 연ꡬ결과: μ½”λ‘œλ‚˜19 ν™•μ§„μžμ˜ μž…μ›κΈ°κ°„μ€ 우츑으둜 꼬리가 κΈ΄ κ°λ§ˆλΆ„ν¬λ₯Ό λ”°λžμœΌλ©°, 평균 μž…μ›κΈ°κ°„μ€ 25.75μΌμ΄μ—ˆλ‹€. ν™•μ§„μžμ˜ 연령은 μž…μ›κΈ°κ°„(0-39μ„Έ: 25.3일(95% 신뒰ꡬ간: 24.6, 26), 40-59μ„Έ: 28.3일(95% 신뒰ꡬ간: 27.6,29.2), 60-79μ„Έ: 26.5일(95% 신뒰ꡬ간: 25.1,27.9), 80μ„Έ+: 26.5일(95% 신뒰ꡬ간: 25.1,27.9))을 λΉ„λ‘―ν•΄μ„œ μ€‘ν™˜μžμ‹€ μ‚¬μš©μ—¬λΆ€(40-59μ„Έ: RR=2.0(95% 신뒰ꡬ간: 1.0,3.7), 60μ„Έ-79μ„Έ: RR=7.4(95% 신뒰ꡬ간: 4.1,13.4), 80μ„Έ+: RR=11.0(95% 신뒰ꡬ간: 5.4,22.3))와 사망여뢀(60-79μ„Έ: RR=5.9(95% 신뒰ꡬ간: 3.4,10.3), 80μ„Έ+: RR=58.6(95% 신뒰ꡬ간: 32.3,106.3))에도 μœ μ˜ν•œ 영ν–₯을 μ£ΌλŠ” 것을 확인할 수 μžˆμ—ˆλ‹€. λ˜ν•œ μž…μ›κΈ°κ°„μ˜ 경우 κΈ°μΉ¨(27.6일(95% 신뒰ꡬ간: 25.2, 26.6); κΈ°μΉ¨ 없을 μ‹œ 25.9일), κ·Όμœ‘ν†΅(27.3일(95% 신뒰ꡬ간: 26.5,28.2); 없을 μ‹œ 26.2일), ꡬ토(27.2일(95% 신뒰ꡬ간: 26.3,28.3); 없을 μ‹œ 26.3일) 여뢀와 같은 μž…μ› μ‹œμ μ—μ„œμ˜ 증상이 μœ μ˜ν•˜κ²Œ 영ν–₯을 μ£ΌλŠ” 것을 확인할 수 μžˆμ—ˆλ‹€. ν•˜μ§€λ§Œ ν™•μ§„μžμ˜ κΈ°μ €μ§ˆν™˜ λ˜λŠ” κ³Όκ±°λ ₯이 μž…μ›κΈ°κ°„μ— μ£ΌλŠ” 영ν–₯은 μœ μ˜ν•˜μ§€ μ•Šμ•˜λ‹€. 반면 μ€‘ν™˜μžμ‹€ μ‚¬μš©μ—¬λΆ€(RR=2.6(95% 신뒰ꡬ간: 1.9,3.6))와 사망여뢀(RR=2.3(95% 신뒰ꡬ간: 1.6,3.1))λŠ” 남성이 여성에 λΉ„ν•΄ μ·¨μ•½ν•œ 것을 확인할 수 μžˆμ—ˆλ‹€. λ˜ν•œ 당뇨(RR=2.2(95% 신뒰ꡬ간: 1.6,3.1)), κ³ ν˜ˆμ••(RR=1.4(95% 신뒰ꡬ간: 1.0,2.0), λ§Œμ„± μ‹ μž₯ μ§ˆν™˜(RR=2.4(95% 신뒰ꡬ간: 1.1,5.1)), μ•”(RR=2.4(95% 신뒰ꡬ간: 1.2,4.4)) λ“±μ˜ κΈ°μ €μ§ˆν™˜κ³Ό κ³Όκ±°λ ₯이 사망에 μœ μ˜ν•œ 영ν–₯을 μ£ΌλŠ” 것을 확인할 수 μžˆμ—ˆλ‹€. κ²°λ‘ : λ³Έ μ—°κ΅¬λŠ” μž…μ›κΈ°κ°„, μ€‘ν™˜μžμ‹€ 이용 및 사망과 κ΄€λ ¨λœ λͺ‡ 가지 인ꡬ톡계학적, μž„μƒμ  νŠΉμ„±μ„ λ°œκ²¬ν–ˆλ‹€. μ΄λŸ¬ν•œ λ°œκ²¬μ€ 의료 μžμ›μ„ 보닀 효율적으둜 λΆ„λ°°ν•  수 μžˆλŠ” 증거λ₯Ό μ œκ³΅ν•  수 μžˆλ‹€.Contents Chapter 1. Introduction 6 Chapter 2. Data and Methods 8 2.1. Data 8 2.2. Methods 10 Chapter 3. Results 11 3.1. Distribution of Hospitalization 11 3.2. Risk Factors for Hospitalization 12 3.3. Risk Factors for Death and ICU 17 Chapter 4. Discussions 22 References 28 List of Tables [Table 3-1~14] 30-42 [Table 4-1~4] 44-47 [Table 5-1~5] 48-52Maste
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