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The Effect of Corporate Social Responsibility on Corporate Image: The Role of Spillover Effect and Negativity Effect based on CSR dimensions (기업의 사회적 책임이 기업 이미지에 미치는 영향 - 차원별 파급효과와 메시지 유형을 중심으로 -)

  • Kim, Seongjin;Kim, Jongkeun
    • Asia Marketing Journal
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    • v.11 no.4
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    • pp.49-67
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    • 2010
  • Previous researches have proven that corporate social responsibility(adhere CSR) is positively related to corporate performance. But Most of CSR related researches have several limitations. One of limitations is that those researches treated CSR as unidimensional construct. Almost researchers in the area of CSR concepts insisted that CSR is consist of multi dimensions. Carroll's four dimensions of CSR have been utilized by numerous academicians. Carroll asserted that CSR is composed of four dimensions: economic, legal, ethical, and philanthropic responsibility. But Carroll's dimensions were revised as three dimensions by Schwartz and Carroll, because ethical and philanthropic responsibility are not mutually exclusive. If CSR construct is composed of multiple dimensions, a message related to one of dimensions changes beliefs or evaluations about other dimensions that are not mentioned in the message. This phenomenon is called as "spillover effect". According to Ahluwalia, Unnava, and Burnkrant, negative information spills over to attributes that are associated with the target attributes but not mentioned in the message. Like this, this preponderant effect of negative information over positive information has been termed the "negativity effect". In this paper, authors try to prove the spillover effect and negativity effect among Schwartz and Carroll's three dimensions(economic, legal, and ethical responsibility) of CSR. The results of this study show that messages related to legal and ethical responsibility cause spillover effect and influence consumers' evaluation to other dimensions. Moreover, when negativity effect is added on spillover effect, spillover effect is more increased. It means that negative messages related to legal and ethical responsibility is more harmful to corporate image than negative message related to economic responsibility. The results of this study will help companies to manage corporate image using CSR messages as marketing communication tools. Companies should manage messages related to legal and ethical responsibility for more efficiently managing corporate image. Specially, because negative messages related to legal and ethical responsibility are more harmful to corporate image, companies must take care not to spread out negative message related to legal and ethical responsibility. Finally, we discuss the implications of the findings and limitations.

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Case Study on Marketing Strategy of E-mart to Be No. 1 Discount Store in Korea (대한민국 1등 할인점을 추구하는 이마트의 마케팅전략에 관한 사례분석)

  • Yoo, Changjo;Ahn, Kwangho;Hwang, Eui Rok
    • Asia Marketing Journal
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    • v.6 no.3
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    • pp.143-156
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    • 2004
  • This case intorduced E-mart's business philosophy and vision, analyzed E-mart's outline of marketing strategy, and discussed its performance and future task. E-mart took the role of market pioneer by developing discount store market in Korea. It's mission was to provide substantial benefits to the customers by selling quality products at the lowest price in the market. For this purpose, E-mart has conducted a slogan of 'everyday low price discount store-E-mart'. Objective of E-mart's brand strategy was to be No. 1 discount store in Korea or to be a representative brand in the discount store market. To achieve this objective, E-mart has conducted various efforts such as construction of national network, realization of the lowest price, formation of the most reliable discount store image, establishment of competitive edge and so on. E-mart settled a new model for discount store in Korea and took the lead in expanding market potential. With these efforts, E-mart has maintained secure position as a leading company in the discount store market.

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Evaluation of the Characteristics of High-Flux Reverse Osmosis Membranes with Various Additives (다양한 첨가제에 따른 고투과성 역삼투막의 특성평가)

  • Hyun Woong Kwon;Kwang Seop Im;Gede Herry Arum Wijaya;Seong Min Han;Seong Heon Kim;Jun Ho Park;Dong Jun Lee;Sang Min Eom;Sang Yong Nam
    • Membrane Journal
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    • v.33 no.6
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    • pp.427-438
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    • 2023
  • In this study, in order to improve the performance of the reverse osmosis membrane with high water flux and high salt rejection, a study was conducted on the evaluation of characteristics according to the curing temperature and time during various additives and interfacial polymerization. The morphology of the membrane with no additives and the membrane with additives both showed a "rigid-and-valley" structure, confirming that the polyamide layer was successfully polymerized on the surface of the porous support layer. In addition, the additive of 2-Ethyl-1,3-hexanediol (EHD) had improved hydrophilicity and water flux, which was confirmed by measuring the contact angle. Finally, a highly permeable TFC membrane with NaCl and MgSO4 salt rejection of 97.78% and 98.7% and a high water flux of 3.31 L/(m2⋅h⋅bar) was prepared.

Development of smart car intelligent wheel hub bearing embedded system using predictive diagnosis algorithm

  • Sam-Taek Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.1-8
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    • 2023
  • If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

Investigating the Smart Hotel Customers' Technology Amenities Adoption Behaviour (스마트호텔 고객의 기술 어메니티 수용에 관한 연구)

  • Kim, Tack Yeon;Chung, Namho
    • Journal of Service Research and Studies
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    • v.13 no.4
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    • pp.142-159
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    • 2023
  • As the core technologies of the 4th Industrial Revolution are introduced into luxury hotels, they are taking off as cultural and experiential spaces that provide new products and services to hotel users and new experiences. Therefore, this study investigated the effect of hotel users' perception of the experience of using technological amenity services on their trust and satisfaction, focusing on luxury hotels as smart hotel to identify the essential factors of smart hotels that can lead to continuous competitive advantage and improvements in the future. In addition, the study aimed to find an effective hotel marketing strategy and plan to satisfaction the smart hotel by maximizing customer satisfaction. To verify the research hypothesis, a survey was conducted targeting hotel users with experience using technological amenities in smart hotels within the last two years. As a result of the study, it was confirmed that all hypotheses were adopted except for the relationship between personification, intention to use technical amenities, and perceived performance expectations and satisfaction with smart hotels. Based on these research results, this paper presents theoretical and practical implications. Smart hotels are rapidly changing by introducing various smart technologies. Therefore, it will be meaningful data for securing a sustainable competitive advantage and establishing differentiated hotel management and marketing strategies.

Implementation and Evaluation of Optimal Dose Control for Portable Detectors with SiPM (SiPM을 통한 휴대용 검출기의 최적 선량 제어에 대한 구현 및 평가)

  • Byung-Wuk Kang;Sun-Kook Yoo
    • Journal of the Korean Society of Radiology
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    • v.17 no.7
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    • pp.1139-1147
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    • 2023
  • The purpose of this paper is to present and evaluate the performance of a method for controlling the dose for optimal image acquisition while minimizing patient exposure by applying a small-sized Photomultiplier(SiPM) sensor inside a portable detector. Portable detectors have the advantage of being able to quickly access the patient's location for rapid diagnosis, but this mobility comes with the challenge of dose control. This paper presents a method to identify the dose that can have the DQE and optimal image quality of the detector through image evaluation based on IEC62220-1-1, an international standard for X-ray imaging devices, and to identify the optimal dose by matching the ADU of the image and the output of the SiPM Sensor. The Skull AP image was acquired by implementing the detector manufacturer's reference dose. The optimal dose was 342.8 µGy, and the optimal controlled dose was 148.3 µGy, which is 57 % of the manufacturer's reference dose. The Chest AP image was 81.9 µGy and the optimal controlled dose was 27.9 µGy, which is a high dose reduction effect of 66 %. In addition, the two images were analyzed by five radiologists and found to have no clinically significant difference in anatomical delineation.

CNN-LSTM-based Upper Extremity Rehabilitation Exercise Real-time Monitoring System (CNN-LSTM 기반의 상지 재활운동 실시간 모니터링 시스템)

  • Jae-Jung Kim;Jung-Hyun Kim;Sol Lee;Ji-Yun Seo;Do-Un Jeong
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.3
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    • pp.134-139
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    • 2023
  • Rehabilitators perform outpatient treatment and daily rehabilitation exercises to recover physical function with the aim of quickly returning to society after surgical treatment. Unlike performing exercises in a hospital with the help of a professional therapist, there are many difficulties in performing rehabilitation exercises by the patient on a daily basis. In this paper, we propose a CNN-LSTM-based upper limb rehabilitation real-time monitoring system so that patients can perform rehabilitation efficiently and with correct posture on a daily basis. The proposed system measures biological signals through shoulder-mounted hardware equipped with EMG and IMU, performs preprocessing and normalization for learning, and uses them as a learning dataset. The implemented model consists of three polling layers of three synthetic stacks for feature detection and two LSTM layers for classification, and we were able to confirm a learning result of 97.44% on the validation data. After that, we conducted a comparative evaluation with the Teachable machine, and as a result of the comparative evaluation, we confirmed that the model was implemented at 93.6% and the Teachable machine at 94.4%, and both models showed similar classification performance.

The Effect of Major Choice Motivation and Academic Achievement on Career Maturity (전공선택동기와 학업성취도가 진로성숙도에 미치는 영향)

  • Eun-Jo Monn;Ji-Won O;Young Seok Kim;Jung Hee Park
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.161-168
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    • 2023
  • This study attempted to determine the relationship between college students' motivation for major selection (personal motivation, social motivation), academic performance, and career maturity, and to identify the influencing factors of career maturity in order to provide basic data for improving career maturity. Data were collected through a structured questionnaire from 199 university students in C city. As a result of examining the correlation between personal motivation for major selection, social motivation, academic achievement, and career maturity, career maturity showed a significant positive correlation with personal motivation for major selection (r=.417, p=.00) and no significant correlation with social motivation for major selection and academic achievement. The influencing factors of career maturity were personal motivation for major selection, economic activity, and major department, and the explanatory power was 24%. Therefore, it seems that university-level support is needed to enable students to engage in economic activities in fields related to their majors. Since personal motivation is important in major selection, we should focus on increasing personal motivation for major selection by providing high school students with a wide range of opportunities, such as career experience and future work experience.

Effect of Calcination Temperature on Electromagnetic Wave Absorption Properties of M-type Ferrite Composite (하소온도가 M형 페라이트 복합재의 전자파 흡수 특성에 미치는 영향)

  • Seong Jun Cheon;Jae Ryung Choi;Sang Bok Lee;Je In Lee;Horim Lee
    • Composites Research
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    • v.36 no.5
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    • pp.289-296
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    • 2023
  • In this study, we investigated the electromagnetic properties and microwave absorption characteristics of M-type hexagonal ferrites, which are known as millimeter-wave absorbing materials, according to their calcination temperature. The M-type ferrites synthesized using a molten salt-based sol-gel method exhibited a single-phase M-type crystal structure at calcination temperatures above 850℃. The synthesized particle size increased as well with the calcination temperature. Saturation magnetization increased gradually with increasing calcination temperature, but coercivity reached a maximum at 1050℃ and then rapidly decreased. After preparing a thermoplastic polyurethane (TPU) composite containing 70 wt% of M-type ferrites, we measured the complex permittivity and permeability in the Q-band (33-50 GHz) and V-band (50-75 GHz) frequency ranges, where ferromagnetic resonance occurred. Strong magnetic loss from ferromagnetic resonance occurred in the 50 GHz band for all composite samples. Based on the measured results, we calculated the reflection loss of the TPU/M-type ferrite composite. By calculating the reflection loss of the M-type ferrite composite, the M-type ferrite calcined at 1250℃ showed excellent electromagnetic wave absorption performance of more than -20 dB at 52 GHz with a thickness of about 0.5 mm.

A Model for Constructing Learner Data in AI-based Mathematical Digital Textbooks for Individual Customized Learning (개별 맞춤형 학습을 위한 인공지능(AI) 기반 수학 디지털교과서의 학습자 데이터 구축 모델)

  • Lee, Hwayoung
    • Education of Primary School Mathematics
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    • v.26 no.4
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    • pp.333-348
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    • 2023
  • Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.