• Title/Summary/Keyword: Global population

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Economic Feasibility Analysis Study to Build a Plant-based Alternative Meat Industrialization Center (식물성 기반 대체육 산업화센터 구축을 위한 경제적 타당성 분석)

  • Yong Kwang Shin;So Young Lee;Jae Chang Joo
    • Journal of Practical Agriculture & Fisheries Research
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    • v.25 no.4
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    • pp.118-126
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    • 2024
  • Recently, the alternative meat (food) market is growing rapidly due to the increase in meat consumption due to global population growth and income improvement, as well as issues such as equal welfare, carbon neutrality, and sustainability. The government is also developing a green bio convergence new industry development plan to foster alternative foods, but there are difficulties in commercialization due to the lack of technology and insufficient production facilities among domestic small and medium-sized enterprises, so it is necessary to build joint utilization facilities and equipment to resolve the difficulties faced by companies. am. In addition, small and medium-sized enterprises are having difficulty developing and commercializing plant-based meat substitutes due to a lack of technical skills, and related equipment is expensive, making it difficult to build equipment on their own. Accordingly, Jeollabuk-do is pursuing a strategy to secure the source technology for development, processing, and industrialization of plant-based substitute meat at the level of developed countries by establishing a plant-based alternative meat industrialization center. In this study, an economic feasibility analysis study was conducted when a plant-based alternative meat industrialization center is built in Jeollabuk-do. As a result of the analysis, B/C=1.32, NPV=374 million won, and IRR=4.8%, showing that there is economic feasibility in establishing an alternative meat industrialization center. In addition, as a result of analyzing the regional economic ripple effect resulting from the establishment of an industrialization center, if 38 billion won is invested in Jeollabuk-do, the nationwide production inducement effect is 74 billion won, the added value inducement effect is 29.8 billion won, and the employment inducement effect is 672 people

Immunomodulatory Effect of Eleutherococcus Senticosus Stem Extract by Cultivars in RAW 264.7 Macrophage Cells (RAW 264.7 대식세포에서 산지별 가시오가피 줄기 추출물의 면역 증강 효과)

  • Ye-Eun Choi;Jung-Mo Yang;Chae-Won Jeong;Hee-Won Yoo;Hyun-Duck Jo;Ju-Hyun Cho
    • Journal of Food Hygiene and Safety
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    • v.39 no.1
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    • pp.44-53
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    • 2024
  • Global interest in natural functional materials to strengthen human immunity is increasing due to the increase in immune-related diseases associated with COVID-19 and the aging population. In this study, we determined the potential therapeutic effect of Eleutherococcus senticosus stems on immune enhancement according to the cultivation region. The contents of eleutheroside B and E, which are chemical components of E. senticosus stems, were analyzed. We showed that the eleutheroside B content of E. senticosus stems in different cultivation regions ranged from 2.96±0.11 to 6.24±0.05 mg/g and from 1.11±0.05 to 2.11±0.03 mg/g in 70% ethanol and hot water extracts, respectively. The eleutheroside E content ranged from 4.93±0.20 to 10.79±0.03 mg/g and 1.75±0.14 to 3.64±0.05 mg/g in 70% ethanol and hot water extracts, respectively. In addition, the immunomodulatory effect of E. senticosus stems was evaluated using RAW 264.7 macrophages. The 70% ethanol extract of E. senticosus stems showed no cytotoxicity up to 200 ㎍/mL, and the hot water extract showed no cytotoxicity up to 500 ㎍/mL. Additionally, the E. senticosus stem extract significantly increased the production of nitric oxide and cytokines (TNF-α, IL-6, and IL-1β) compared to their production in the control group. These results suggest that E. senticosus stem extracts are a potential functional food material and ingredient to enhance the immune response.

Surrogate Internet Shopping Malls: The Effects of Consumers' Perceived Risk and Product Evaluations on Country-of-Buying-Origin Image (망상대구점(网上代购店): 소비자감지풍험화산품평개대원산국형상적영향(消费者感知风险和产品评价对原产国形象的影响))

  • Lee, Hyun-Joung;Shin, So-Hyoun;Kim, Sang-Uk
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.2
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    • pp.208-218
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    • 2010
  • Internet has grown fast and become one of the most important retail channels now. Various types of Internet retailers, hereafter etailers, have been introduced so far and as one type of Internet shopping mall, 'surrogate Internet shopping mall' has been prosperous and attracting consumers in the domestic market. Surrogate Internet shopping mall is a unique type of etailer that globally purchases well-known brand goods that are not imported in the market, completes delivery in the favor of individual buyers, and collects fees for these specific services. The consumers, who are usually interested in purchasing high-end and unique but not eligible brands, have difficulties to purchase these items overseas directly from the retailers or brands in other countries due to worries of payment failure and no address available for their usually domestic only delivery. In Korea, both numbers of surrogate Internet shopping malls and the magnitude of sales have been growing rapidly up to more than 430 active malls and 500 billion Korean won in 2008 since the population of consumers who want this agent shopping service is also expending. This etail business concept is originated from 'surrogate-mediated purchase' and this type of shopping agent has existed in many different forms and also in wide ranges of context level for quite a long time. As marketers face their individual buyers' representatives instead of a direct contact with them in many occasions, the impact of surrogate shoppers on consumer's decision making has been enormously important and many scholars have explored various range of agent's impact on consumer's purchase decisions in marketing and psychology field. However, not much rigorous research in the Internet commerce has been conveyed yet. Moreover, since as one of the shopping agent surrogate Internet shopping malls specifically connect overseas brands or retailers to domestic consumers, one specific character of the mall's, image of surrogate buying country, where surrogate purchases are conducted in, may play an important role to form consumers' attitude and purchase intention toward products. Furthermore it also possibly affects various dimensions of perceived risk in consumer's information processing. However, though tremendous researches have been carried exploring the effects of diverse dimensions of country of origin, related studies in Internet context has been rarely executed. There have been some studies that prove the positive impact of country of origin on consumer's evaluations as one of information clues in product manufacture descriptions, yet studies detecting the relationship between country image of surrogate buying origin and product evaluations rarely undertaken regarding this specific mall type. Thus, the authors have found it well-worth investigating in this specific retail channel and explored systematic relationships among focal constructs and elaborated their different paths. The authors have proven that country image of surrogate buying origin in the mall, where surrogate malls purchase products in and brings them from for buyers, not only has a positive effect on consumers' product evaluations including attitude and purchase intention but also has a negative effect on all three dimensions of perceived risk: product-related risk, shipping-related risk, and post-purchase risk. Specifically among all the perceived risk, product-related risk which is arisen from high uncertainty of product performance is most affected (${\beta}$= -.30) by negative country image of surrogate buying origin, and also shipping-related risk (${\beta}$= -.18) and post-purchase risk (${\beta}$= -.15) get influenced in order. Its direct effects on product attitude (${\beta}$= .10) and purchase intention (${\beta}$= .14) are also secured. Each of perceived risk dimension is proven to have a negative effect on purchase intention through product attitude as a mediator (${\beta}$= -.57: product-related risk ${\rightarrow}$ product attitude; ${\beta}$= -.24: shipping-related risk ${\rightarrow}$ product attitude; ${\beta}$= -.44: post-purchase risk ${\rightarrow}$ product attitude) as well. From the additional analysis, the paths of consumers' information processing are shown to be different based on their levels of product knowledge. While novice consumers with low level of knowledge consider only perceived risk important, expert consumers with high level of knowledge take both the country image, where surrogate services are conducted in, and perceived risk seriously to build their attitudes and formulate decisions toward products more delicately and systematically, which is in line with previous studies. This study suggests several pieces of academic and practical advice. Precisely, country image of surrogate buying origin does affect on consumer's risk perceptions and behavioral consequences. Therefore a careful selection of surrogate buying origin is recommended. Furthermore, reducing consumers' risk level is required to blossom this new type of retail business whether its consumer are novices or experts. Additionally, since consumer take different paths of elaborating information based on their knowledge levels, sophisticated marketing approaches to each group of consumers are required. For novice buyers strong devices for risk mitigation are needed to induce them to form better attitudes and for experts selections of better and advanced countries as surrogate buying origins are advised while endorsement strategy for the site might work as a reliable information clue to all consumers to mitigate the barriers to purchase goods online. The authors have also explained that the study suffers from some limitations, including generalizability. In future studies, tests of and comparisons among different types of etailers with relevant constructs are recommended to broaden the findings.

A Methodology of Customer Churn Prediction based on Two-Dimensional Loyalty Segmentation (이차원 고객충성도 세그먼트 기반의 고객이탈예측 방법론)

  • Kim, Hyung Su;Hong, Seung Woo
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.111-126
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    • 2020
  • Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.