• New & Renewable Energy
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• v.18 no.3
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• pp.43-59
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• 2022

The green premium is the most important feature of Korea's RE100 system. Green premium has three characteristics. The first, the cost of implementation is lower than that of other means of implementation. The second, it is linked with the RPS system to keep the means of implementing the green premium low. Third, the funds raised by the green premium are used to supply renewable energy to compensate for the additionality that the green premium does not have. When the entire industrial sector's electricity consumption is converted to renewable energy, the implementation cost of the green premium is estimated to be 3,377.4 billion won, and the REC purchase is estimated to incur the implementation cost of 6,576.4 billion won, which is 3.5 trillion more than the green premium. It was analyzed that an additional implementation cost of KRW 100 million would occur. In addition, in the case of solar PPA, it was analyzed that additional implementation costs of KRW 13,375.7 billion to KRW 16,162.3 billion were incurred. It was estimated that the renewable energy that could be supplied to the green premium would at least be sufficient for companies exporting to the US and EU. In addition, it was analyzed that when the fund created as a green premium is used for renewable energy supply, about 30.7% of the renewable energy supply through PPA can be supplied. However, as ESG is emphasized, green premium can be criticized by green washing because there is no additionality. There is also a limit to responding to the EU's CBAM. Therefore, companies can use the green premium depending on the situation, but it is more advantageous to use PPA, etc. The government needs to sufficiently maintain the supply of renewable energy using the fund to maintain the green premium.

• Journal of Korea Trade
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• v.27 no.3
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• pp.43-64
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• 2023

Purpose - This paper studies whether CISG can be a suitable governing law for pure service contracts. When CISG was first drafted, there was little disagreement on the fact that contracts for the sale of goods and those for the provision of services were two different types of contract. Based on this understanding, CISG explicitly provides that the Convention will apply to contracts where the preponderant part of the contractual obligation is on the sale of goods, not services. However, as more sales transactions have come to include more elements of services, mainly due to the advancement of the IoT industry, the distinction between goods and services became more blurred. Based on the observation of recent changes, some scholars even argue that such a change supports the applicability and suitability of CISG to even pure service contracts. The purpose of this paper is to critically analyze and evaluate their argument. Design/methodology - This paper focuses on two separate but related issues: CISG's 'applicability' and 'suitability' to service contracts. For the first issue, this paper will examine the rules of interpretation of international treaties under the Vienna Convention on the Law of Treaties of 1969, and will apply its rules to find the proper answer. For the second issue, this paper will perform logical and empirical analyses on the reasoning employed by scholars claiming the suitability of CISG to service contracts. Findings - This paper concludes that CISG does not, and should not, apply to pure service contracts. The argument that CISG applies to pure service contracts directly contravenes Article 3(2) of the Convention, which expressly states that it does not apply to a contract wherein the preponderant part of its obligation is about services rather than sales. Similarly, CISG is not a suitable governing law for pure service contracts because it aims provide rules specifically tailored to the needs of transactions of sales of goods, not services. Servitization of sales of goods transaction does not change this conclusion. Originality/value - This paper presents different views from those offered by some eminent scholars on the issue of applicability and suitability of CISG to service contracts. By doing so, it is hoped that the confusion caused in discussions so far are clarified. Hopefully, this paper can also provide practical guidance to practitioners engaged in the fields of international sales, services, and IoT industries.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.1-25
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• 2011

Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

• The Journal of Industrial Distribution & Business
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• v.1 no.1
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• pp.23-31
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• 2010

In this study, market orientation affects the real estate transaction and about the various parameters examined, the real estate transactions, market orientation and intensity of competition in the market upheaval and the impact was seen on the results can be summarized as follows. First, market orientation and about the relationship between real estate transactions were examined. Each variable of customer satisfaction information generation, information dissemination, information was used for the reaction. Among them, the dissemination of information, information about the reaction produces a lot better the customer satisfaction was the result. In other words, the dissemination of information and availability of information to real estate transactions, the more you can improve customer satisfaction. While the information does not appear to be generated as a result of the impact of market orientation when the first phase of the creation of market information and the customer's needs and preferences of current and future information and external factors affecting them to gather information about It is difficult to assess realistically can be seen. This is both our customers and dealers in real estate purchase or trade items for the exact targets, but the general approach the start of trading because by necessity. Therefore, a clear standard for real estate deals in and nine minutes to all sellers of real estate purchases through a process of communication to enable effective approach should be. Second, market orientation and about the relationship between real estate transactions were examined. The information for each variable in re-creating transactions, information dissemination, information was used for the reaction. Variable affects all the information creation, dissemination of information, information about the reaction the better the deal re-done show that two can be frequent. In other words, information generation, information dissemination and utilization of information to real estate transactions, the more customers the added responsibilities of the re-trade can be seen. Third, the relationship between market orientation and in the real estate market upheaval of environmental factors on the relationship between gender were examined. Each variable of customer satisfaction information generation, information dissemination, information was used for the reaction. Among them, the dissemination of information, information about the reaction produces a lot better the customer satisfaction was the result. In other words, the dissemination of information, depending on the market upheaval and the availability of information to raise the real estate can increase customer satisfaction. Fourth, market orientation and environmental factors in the relationship between real estate transactions and about the relationship between competition intensity was investigated. The information for each variable in re-creating transactions, information dissemination, information was used for the reaction. Variable affects all the information creation, dissemination of information, information about the reaction the better the deal re-done show that two can be frequent. In other words, information generation, information dissemination and utilization of information and the higher intensity of competition or unyounghameusseo ttaemaewoo active real estate transactions to provide our customers the added responsibilities of the re-trade can be seen. If more comprehensive, market orientation, according to real estate transactions and environmental factors affecting the performance was also different. Abundance of information about the current real estate it is true that the accuracy and reliability, and real estate, and are unsure about the expected benefits. So you want to trade to provide accurate information to customers and markets change rapidly and competition is severe, with more information if you have reliable information to the customer must supply can increase trading performance. Guarantee of future customer transactions and can provide valuable information and research needs to be differentiated based on the provision of real estate information should be done to achieve profitability will be a cow brokerage.

• Archives of design research
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• v.14 no.1
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• pp.63-70
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• 2001

Thanks to the inter-connection of information servers throughout the world based on the internet technology, the new sphere which actual transaction can be made like in the visible market has become conspicuous as the virtual space. The movement to realize the new business through the cyber space has been actively ongoing. In the domestic market, a lot of corporations knowing the needs of internet shopping malls have entered into this e-business but they have not made a big success comparing with internet's potentials. And, it can be attributed to the simple planes and the limitations of information provided by the cyber malls, which means that the needs of better information transfer we apparent Accordingly, in this thesis, the research on the 3-D based products and shopping malls has been made through the inter-complementary composition between the 2-D shopping malls and 3-B ones. This research consists of 3 parts. Firstly, through the research on references and existing data, it presents the analysis on consumer's characteristics and sales limits of the internet shopping mall's products. Secondly, the background of 3-D shopping mall's advent and the virtual reality technology data are put together. Finally, it presents how the development of 3-D based product modeling and shopping malls can increase the consumer's purchase power and furthermore the directions of shopping malls to go.

• Culinary science and hospitality research
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• v.6 no.1
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• pp.57-78
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• 2000

In the 21st century the size of sales of food service business in Korea will be 30 trillion won which means Food service business in Koreas is a mega market, but it is only quantitative growth and might face the limit of growth. At the same time it is predicted that from the academic world Food service business will develop endlessly after IMF condition. Of course I hope so as a member of national. Al though I propose that quantitative side is important, qualitative side must not be disregarded the present and future customer is needs should be met because the 1st goal of company is to achieve a management goal and pursuit profit. The present situation requires a peculiar and specific strategy of its own which can not be followed by competing hotels so that value can be created and buying intention can be occurred after buying. Until now the goal of marketing campaign has been transacted marketing just for closing a transaction, but it must be related marketing which is seeking mutual interests of customer and company. The strategies to attain these goals are : 1) to change from products and service management-focused to customer management and relationship building-focused. 2) to establish a core strategy which needs to be changed from market occupancy of volume expansion to customer occupancy. 3) to change from one-way communication to two-way communication. 4) to change from large scale marketing by company dimension to small scale marketing by sections. If companies focus on core benefit and augmented service to be sought by customers and make every efforts to create a value customer occupancy will increase automatically, the reduction of marketing cost will be followed, and marketing efforts will be much more efficient. In introducing a new product it is still easier to diffuse through the existing customers, and also important market information can be obtained from customers using this close relationship. If this close relationship maintains well customers will say even a trivial inconvenience and complaint and propose an idea of new product. Kotler divides relationship marketing into 5 stages such as Basic, Reactive, Accountable, Proactive, and Partnership. From the 1st stage to the last stage customer management is absolutely important and also in management strategy. The last stage, Partnership can come into the stage which is actively participated in service development and problem solving by customers. so more loyal customers have more successful performance the company attain.

• The Journal of Information Systems
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• v.30 no.1
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.102-116
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• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.