6 research outputs found
A Review of Marketing Literature on Market Responses to Product Harm Crises
λ³Έ λ
Όλ¬Έμμλ μ ν κ²°ν¨ μκΈ° λ°μμ λ°λ₯Έ μμ₯ λ°μ μΈ‘λ©΄μ λ§μΌν
λ¬Ένμ μ€μ¬μΌλ‘ μ΄ν΄λ³΄κ³ , μλΉμμ μ¬λ¦¬μ μ²λ¦¬ κΈ°μ λ₯Ό λΆμν μ€ν μ°κ΅¬ λ° μλΉμμ μ€μ ꡬ맀 νλμ λΆμν κ³λ μ°κ΅¬λ₯Ό λ€μνκ² μ΄ν΄λ³΄μλ€. μλΉμμ μΈκ΅¬ν΅κ³μ νΉμ±μ λ°λΌ κ·Έλ¦¬κ³ μλΉμμ μ¬μ κΈ°λμ λ°λΌ μ ν κ²°ν¨ μκΈ°μ λν λ°μμ΄ λ€λ₯΄λ€. λν μ ν κ²°ν¨ μκΈ°μ μμΈμ μ§λ¨νλ μλΉμμ μ¬λ¦¬μ μ²λ¦¬ κΈ°μ μ μ°¨μ΄μ λ°λΌ λ°μμ΄ μμ΄ν¨μ μ¬λ¬ μ°κ΅¬μμ μ μνκ³ μμμ μ΄ν΄λ³΄μλ€. μ ν κ²°ν¨ μκΈ°κ° κΈ°μ
μ κ΄κ³ νλμ ν¨κ³Ό, μλΉμμ κ°κ²© λ―Όκ°λ λ± λ§μΌν
νλμ ν¨κ³Όμ μ΄λ ν μν₯μ λ―ΈμΉλμ§μ λν μ°κ΅¬λ μ΄ν΄λ³΄μλ€.
κΈ°μ‘΄μ λ§μΌν
μ°κ΅¬ λ¬Ένλ€μ΄ κΉμ΄ λ°νμ§ λͺ»ν λ€μκ³Ό κ°μ λΆμΌλ₯Ό μΆν μ°κ΅¬κ° λ μ΄λ£¨μ΄μ ΈμΌ ν λ°©ν₯μΌλ‘ μ μνλ€. λ¨Όμ , μλΉμμ λ€μν νΉμ±μ λ°λ₯Έ λ°μ μ΄μ§μ±μ λν μ°κ΅¬κ° νμνλ€. λμ§Έ, μ ν κ²°ν¨ μκΈ° λ°μ ν μ λ’° ν볡과 κ΄λ ¨λ νλ‘μΈμ€μ λν μλΉμμ λ―Έμμ νλ μΈ‘λ©΄μμ μ΄λ€ κ³Όμ μ κ±°μ³ μλΉμλ€μ΄ κ²°ν¨μ΄ λ°μν λΈλλμ λν΄ μ λ’°λ₯Ό ν볡νλμ§, νΉμ μ΄λ€ 쑰건μμ μ λ’°κ° ν볡λλμ§μ λν μ°κ΅¬κ° μ΄λ£¨μ΄μ§ νμκ° μλ€. μ
μ§Έ, μ ν κ²°ν¨ μκΈ°μ λ°λΌ μλΉμλ€μ μ ν κ΄λ ¨ νλμ νλμ΄ μκΈ° λ°μ μ μμ€μΌλ‘ ν볡λκΈ°κΉμ§ 걸리λ μκ°μ μ ν μ νλ³, μλΉμ μ νλ³, μ ν-μλΉμ κ΄κ³ μ νλ³ λ±μΌλ‘ ꡬλΆνμ¬ μ’ λ κΉμ΄ μ΄ν΄ν νμκ° μλ€. λ§μ§λ§μΌλ‘, κ΄κ³ μ λλΆμ΄ μ΄μ§μ μΈ‘λ©΄μμ μ΄λ€ μ΄μ§ νλμ΄ μ ν¨νμ§ μ΄λ ν 맀체λ₯Ό ν΅ν μ΄μ§ νλμ΄ μμ©μ±μ΄ λμμ§ λ±μ μ°κ΅¬κ° νμνλ€κ³ νλ¨λλ€.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΅¬λ μμΈλνκ΅ κ²½μμ°κ΅¬μμ μ°κ΅¬λΉ μ§μμ λ°μ μνλμλ€
Predictive Modeling of Customers Insurance Purchase Behaviors
λ³Έ λ
Όλ¬Έμ μ€μ μ€λ¬΄μ(practitioner)μ μν΄μ, κ·Έλ¦¬κ³ νκ³ νΉμ μ°κ΅¬μ(academics)μ μν΄μ μ μΌ λ§μ΄ μ°μ΄λ μ‘°μ§λ¬Έν μΈ‘μ λκ΅¬κ° λ¬΄μμ΄κ³ , κ·Έκ²μ ꡬ체μ νμ©λ°©λ²μ 무μμΈμ§ νμ
Β·μ λ¬νλ λ° λͺ©μ μ΄ μλ€.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΅¬λ μμΈλνκ΅ κ²½μμ°κ΅¬μμ μ°κ΅¬λΉ μ§μμ λ°μ μνλμλ€
μ½λ‘λ19μ μ μκΈ°κ°: κ΅λ΄ κ°μΈμμ€ μ°κ΅¬
νμλ
Όλ¬Έ (μμ¬) -- μμΈλνκ΅ λνμ : 보건λνμ 보건νκ³Ό(보건νμ 곡), 2021. 2. κΉνΈ.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.μ°κ΅¬λ°°κ²½: 2020λ
1μ 첫 νμ§μ μ΄ν, λνλ―Όκ΅μ μ½λ‘λ19 μ νμ λμ΄μ§ μκ³ μλ€. μ΄λ‘ μΈν΄ λ³μ λ± νμ λ μλ£μμμ λΆμ‘±μ΄ μ¬κ°ν λ¬Έμ λ‘ λλλκ³ μλ€. μ΄μ λ³Έ μ°κ΅¬λ μ§λ³κ΄λ¦¬λ³ΈλΆκ° μ 곡νλ μ κ΅λ¨μ κ°μΈμμ€ μμμλ£μΈ μ½λ‘λ19 νμ§μ μμμνμ 보λ₯Ό μ΄μ©νμ¬ μ½λ‘λ19 νμ§μμ μ
μκΈ°κ° λ° μ€νμμ€ μ¬μ©, μ¬λ§μ¬λΆ λ±κ³Ό μκ΄μ΄ μλ λ³μλ₯Ό νμ
ν¨μΌλ‘μ λ³΄λ€ ν¨μ¨μ μΈ μλ£μμ λΆλ°°μ κΈ°μ¬νκ³ μ νλ€.
μ°κ΅¬λ°©λ²: λ³Έ μ°κ΅¬λ μ½λ‘λ19 νμ§μ μμμνμ 보λ₯Ό μ΄μ©νμ¬ μ½λ‘λ19 νμ§μκ° λ³΄μ ν μνμμΈλ€κ³Ό μ
μκΈ°κ°, μ€νμμ€ μ¬μ©μ¬λΆ, κ·Έλ¦¬κ³ μ¬λ§μ¬λΆμ κ΄κ³λ₯Ό νμΈνλ€. μ΄λ₯Ό μν΄μ κ°λ§ λΆν¬ μΌλ°ν μ νλͺ¨νμ μ¬μ©νμλ€.
μ°κ΅¬κ²°κ³Ό: μ½λ‘λ19 νμ§μμ μ
μκΈ°κ°μ μ°μΈ‘μΌλ‘ κΌ¬λ¦¬κ° κΈ΄ κ°λ§λΆν¬λ₯Ό λ°λμΌλ©°, νκ· μ
μκΈ°κ°μ 25.75μΌμ΄μλ€. νμ§μμ μ°λ Ήμ μ
μκΈ°κ°(0-39μΈ: 25.3μΌ(95% μ 뒰ꡬκ°: 24.6, 26), 40-59μΈ: 28.3μΌ(95% μ 뒰ꡬκ°: 27.6,29.2), 60-79μΈ: 26.5μΌ(95% μ 뒰ꡬκ°: 25.1,27.9), 80μΈ+: 26.5μΌ(95% μ 뒰ꡬκ°: 25.1,27.9))μ λΉλ‘―ν΄μ μ€νμμ€ μ¬μ©μ¬λΆ(40-59μΈ: RR=2.0(95% μ 뒰ꡬκ°: 1.0,3.7), 60μΈ-79μΈ: RR=7.4(95% μ 뒰ꡬκ°: 4.1,13.4), 80μΈ+: RR=11.0(95% μ 뒰ꡬκ°: 5.4,22.3))μ μ¬λ§μ¬λΆ(60-79μΈ: RR=5.9(95% μ 뒰ꡬκ°: 3.4,10.3), 80μΈ+: RR=58.6(95% μ 뒰ꡬκ°: 32.3,106.3))μλ μ μν μν₯μ μ£Όλ κ²μ νμΈν μ μμλ€. λν μ
μκΈ°κ°μ κ²½μ° κΈ°μΉ¨(27.6μΌ(95% μ 뒰ꡬκ°: 25.2, 26.6); κΈ°μΉ¨ μμ μ 25.9μΌ), κ·Όμ‘ν΅(27.3μΌ(95% μ 뒰ꡬκ°: 26.5,28.2); μμ μ 26.2μΌ), ꡬν (27.2μΌ(95% μ 뒰ꡬκ°: 26.3,28.3); μμ μ 26.3μΌ) μ¬λΆμ κ°μ μ
μ μμ μμμ μ¦μμ΄ μ μνκ² μν₯μ μ£Όλ κ²μ νμΈν μ μμλ€. νμ§λ§ νμ§μμ κΈ°μ μ§ν λλ κ³Όκ±°λ ₯μ΄ μ
μκΈ°κ°μ μ£Όλ μν₯μ μ μνμ§ μμλ€. λ°λ©΄ μ€νμμ€ μ¬μ©μ¬λΆ(RR=2.6(95% μ 뒰ꡬκ°: 1.9,3.6))μ μ¬λ§μ¬λΆ(RR=2.3(95% μ 뒰ꡬκ°: 1.6,3.1))λ λ¨μ±μ΄ μ¬μ±μ λΉν΄ μ·¨μ½ν κ²μ νμΈν μ μμλ€. λν λΉλ¨(RR=2.2(95% μ 뒰ꡬκ°: 1.6,3.1)), κ³ νμ(RR=1.4(95% μ 뒰ꡬκ°: 1.0,2.0), λ§μ± μ μ₯ μ§ν(RR=2.4(95% μ 뒰ꡬκ°: 1.1,5.1)), μ(RR=2.4(95% μ 뒰ꡬκ°: 1.2,4.4)) λ±μ κΈ°μ μ§νκ³Ό κ³Όκ±°λ ₯μ΄ μ¬λ§μ μ μν μν₯μ μ£Όλ κ²μ νμΈν μ μμλ€.
κ²°λ‘ : λ³Έ μ°κ΅¬λ μ
μκΈ°κ°, μ€νμμ€ μ΄μ© λ° μ¬λ§κ³Ό κ΄λ ¨λ λͺ κ°μ§ μΈκ΅¬ν΅κ³νμ , μμμ νΉμ±μ λ°κ²¬νλ€. μ΄λ¬ν λ°κ²¬μ μλ£ μμμ λ³΄λ€ ν¨μ¨μ μΌλ‘ λΆλ°°ν μ μλ μ¦κ±°λ₯Ό μ 곡ν μ μλ€.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