• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.261-290
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• 2022

Although market stabilization measures have been triggered in the K-ETS, carbon price is still under uncertainty. Considering Korea's 2030 enhanced reduction target announced in October 2021, it is crucial to have practical stabilization measures to appropriately deal with price uncertainty. This study examines the quantitative effects of a price collar, which is considered as a means of alleviating price uncertainty, on expected cumulative emissions and abatement costs. There are three main scenarios: carbon tax, emissions trading system, and emissions trading system with a price collar. Monte Carlo simulation was conducted to reflect uncertainty in emission. There are several results as follows: 1) In a price collar, domestic emission target is likely to be achieved with a lower expected abatement cost than other scenarios. In addition, there is a small amount of excess emissions in this research and it would be not critical(0.1% excess than target); 2) Prohibiting banking increases the expected abatement cost. This is because firms can not intertemporally reallocate allowances to match the firm's optimal emissions path; 3) With the adoption of a price collar, government's net revenue can be positive even if the government's purchase volume of emissions allowances is more than sales volume. This is because the government sells them at price ceiling and purchases them at price floor.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.531-546
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• 2022

This study analyzes the performance and characteristics of the fostering policies for the focusing on growth path and type occupied in the Technoparks. First, the companies occupied in the Technoparks have shown the characteristics of landing on an actual growth phase beyond the start-up and fostering phases, and when considering the possession of a dedicated R&D organization and the portion of highly educated technical personnel having masters and doctorate degrees, these companies have also entailed the characteristics of being a technological innovation company. Second, about 30% of the companies that left the Technoparks secured their own factories and offices after standing alone, indicating that the fostering function after startup in the Technoparks has been performing a significant role on the growth path of start-up companies from a temporal perspective. Third, a majority of the companies occupied in the Technoparks were composed of scale-up companies or preliminary scale-up companies that contained promising innovative growth potential. However, it seems to urgently require the acceleration of innovation because many companies are categorized into a stagnated growth type that demonstrates a high R&D investment but low sales revenue growth.

• Asia Marketing Journal
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• v.13 no.3
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• pp.233-248
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• 2011

This case illustrates a story of passionate and innovative new market development by Pulmuone, a fresh food provider in Korea. The company has been successfully developing a new market by introducing a (non-frying) fresh ramen, 'Jayeonun Masitda - The Nature Is Tasty' in the packaged ramen market dominated by fried ones. In this case, a detailed new market development process by Pulmuone will be investigated including; company overview, a new product development process, marketing strategy formulation, marketing mix implementation, market performance, and future directions. Pulmuone has been making efforts to create a new product category by marketing non-frying ramens since 1995, but with a modest success. In 2011, Pulmuone finally succeeded to develop an innovative product, 'Jayeonun Masitda' that brought more health and nutrition conscious consumers' attention in the ramen market. The company intended to change the current competitive structure in the ramen market, i.e., from the strength of taste and the amount of ingredient to fried/non-fried and the freshness of ingredient. By this new positioning, Pulmuone aimed to reshaping the ramen market into competition between healthy and unhealthy ramens. Pulmuone has been successful in developing a new market. Sales revenue of 'Jayeonun Masitda' has been continuously increasing, and customers are found to be highly satisfied with the product resulting in a high repeat purchase rate. The company's successful new market development can be attributed to a faithful new product development process, innovative technology, an appropriate positioning strategy, and consistent marketing communication. In addition, Pulmuone's eco-friendly corporate image and the organization's passion to grow are also important factors for success of this new market development.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.109-121
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• 2024

This paper adopts a resource-based approach to analyze why some universities have a greater number of faculty startups, and how this impacts on performance, in terms of indictors such as the number of employees and revenue sales. More specifically, we propose 9 hypotheses which link institutional resources to faculty startups and their performance, and compare 5 different groups of university resources for cross-college variation, using data from 134 South Korean four-year universities from 2017 to 2020. We find that the institutional factors impacting on performance of faculty startups differ from other categories of startups. The results show that it is important for universities to provide a more favorable environment, incorporating more flexible personnel policies and accompanying startup support infrastructure, for faculty startups, whilest it is more effective to have more financial resources and intellectual property for other categories of startups. Our findings also indicate that university technology-holding company and technology transfer programs are crucial to increase the number of faculty startups and their performance. Our analysis results have implications for both university and government policy-makers, endeavoring to facilitate higher particaption of professors in startup formation and ultimate commercialization of associated teachnologies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.155-165
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• 2024

Software as a Service (SaaS) has become one of the fastest-growing software business models in recent years. Even during the economic downturn following the pandemic, the SaaS business has emerged as a crucial model for IT companies. The revenue structure of SaaS, which is based on the subscription economy model, ensures that users pay only for the services used. In other words, SaaS operates on a subscription-based billing model, thus providing subscribers access to software uploaded to cloud computers via the Internet. This study aimed to explore the manner by which software-solution firms have to counteract the decline in profit and loss sales caused by changing their business-model orientation from on-premise deployment software to subscription-based software. Additionally it analyzes a method for selecting a subscription-based pricing model and rapidly recovering the investment costs via quantitative business-viability assessment. By calculating subscription fees via a more quantitative business-viability evaluation instead of focusing on conventional business-planning methods that rely on qualitative methods, companies are expected to be equipped in providing services to customers at reasonable costs. This strategy will facilitate them in leading emerging growth sectors.

• Asia Marketing Journal
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• v.13 no.3
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• pp.79-102
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• 2011

Researchers in channel dyads have devoted much attention to relationship between interdependence (i.e. interdependence enymmetry and total interdependence) and conflict that promote channel performance. In social science, in spite of the inconsistent results in marketing practice, there are two contradictory theories explain the relationship between interdependence and conflict - bilateral deterrence theory and conflict spiral theory. The authors apply these theories to co-marketing alliance situation in terms that this relationship is also incorporated both company's dependence, either from one company's perspective or each partner about its respective dependence. Using survey data and archival data from 181 companies enlisted in a telecommunication membership program, the authors find out the relationship between interdependence and conflict as well as investigate the antecedents of interdependence - transaction age, transaction frequency, the numbers of alliance partner, and co-marketing alliance specific assets according to previous researches. Using PLS analysis, the authors demonstrate that, with increasing total interdependence in a telecommunication membership program, two co-marketing partners' conflict level is increased in accord with the author's conflict spiral theory predictions. As expected, higher interdependence asymmetry has negative value to level of conflict even though this result is not statistically significant. Other findings can be summarized as follows. In the perspective of telecommunication company, transaction age, transaction frequency, and co-marketing alliance specific assets have influence on its dependence on a partner as independent variables. To the contrary, in a partner's perspective, transaction frequency, co-marketing alliance specific assets and the numbers of alliance partner have significantly impact on its dependence on a telecommunication company. In direct effect analysis, it is shown that transaction age, frequency and co-marketing alliance specific assets have direct influence on conflict. This results suggest that it is more useful for a telecommunication company to select a co-marketing partner which is frequently used by customers and earned high rates of mileage. In addition, the results show that dependence of a telecommunication company on a co-marketing partner is more significantly effected to co-marketing alliance conflict than partner's one. It provide an effective conflict management strategy to a telecommunication company for controling customer's usage rate or having the co-marketing partner deposit high level of alliance specific investment (i.e. mileage). To a co-marketing partner of telecommunication company, it is required control the percentage of co-marketing sales in total sales revenue or seek various co-marketing partners in order for co-marketing conflict management. The research implications, limitation and future research of these results are discussed.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.67-83
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• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.12 s.159
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• pp.1697-1707
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• 2006

Relentless advances in information technology are constantly transforming market dynamics of the retail industry. RFID is an emerging innovative technology that can reduce labor costs, improve inventory control and increase sales by effective business processes. Apparel retailers need to recognize the benefits of RFID and identify critical success factors. By focusing on apparel retailers, this study attempts (1) to identify the reality of RFID associated with benefits; and (2) to prospect the implementation of RFID in apparel retailing. We conducted a focus group interview with selected six panels who were experts of retail industry in the United States to obtain data regarding RFID attributes. Content analysis was used to generate related excerpts and classify 31 attributes of RFID benefits from the meaningful 173 responses. For experience of RFID, retailers were familiar with RFID technology and expressed the belief that RFID basically would support an existing retail system for speed to markets. However, retailers addressed the level of experience with RFID technology that they were still in the early adoption stage among few innovative companies. The content analysis identified five dimensions of RFID benefits for apparel retailing: Visibility and Velocity, Revenue Enhancement, Customer Service, Security, and Employee Productivity. This result lends support to the belief that RFID has a significant potential to streamline supply chain management, store operation and customer service for apparel retailing. This study provides intellectual and managerial implications far practitioners and researchers by postulating the effective use of RFID in the apparel retail industry.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.