• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
• /
• 2006.06b
• /
• pp.305-309
• /
• 2006

This paper presents and illustrates the application of a growth and yield model that supports both forest and mill side volume and value estimates. Traditional forest stand growth and yield models represent the forest landowner view of yield and economics. Predicted yields are estimates of what one would expect from a procurement cruise, and current stumpage prices are applied to investigate optimum management strategies. Optimum management regimes and rotation ages obtained from the forest side view are unlikely to be economically optimal when viewed from the mill side. The actual distribution of recoverable manufactured product and its value are highly dependent on mill technologies and configurations. Overcoming this limitation of growth and yield computer models necessitates the ability to predict and price the expected manufactured distribution of lumber, lineal meters of veneer, and tonnes of air dried pulp fiber yield. With these embedded models, users of the yield simulator can evaluate the economics of possible/feasible management regimes from both the forest and mill business sides. The simulator is a forest side model that has been modified to produce estimates of manufactured product yields by embedding models for 1) pulpwood chip size class distribution and pulp yield for any kappa number (Schultz and Matney, 2002), 2) a lumber yield and pricing model based on the Best Opening Face model developed by the USDA Forest Service Forest Products Laboratory (Lewis, 1985a and Lewis, 1985b), and 3) a lineal meter veneer model derived from peeler block tests. While the model is strictly applicable to planted loblolly pine (Pinus taeda L.) on cutover site-prepared land in the United States (US) Gulf South, the model and computer program are adaptable to any region and forest type.

• Journal of dental hygiene science
• /
• v.22 no.4
• /
• pp.241-248
• /
• 2022

Background: Plastic waste generates pollutants in the process of incineration or landfilling, and accumulates in water or marine organisms, causing adverse effects on the environment and the human body. Recently, various eco-friendly oral hygiene products (Eco-OHPs) such as bamboo toothbrushes and biodegradable plastic toothbrushes have been developed. Therefore, this study aimed to investigate the current level of awareness and purchasing status of eco-OHPs among adults who are interested in eco-friendly products. Methods: This study included adults aged >19 years who regularly visited eco-friendly shops and online sites; the online survey links were distributed during their visits to eco-friendly Internet cafés and companies. Of the 22 questions, seven assessed the participants' general characteristics, three assessed the general oral hygiene care products used, six assessed the level of awareness of Eco-OHPs, and six assessed the purchasing status of Eco-OHPs. Frequency analysis, chi-square test, and regression analysis were performed using SPSS software. Results: Among the respondents, 108 (51.4%) were aware of Eco-OHPs, and 79 (37.6%) had experience purchasing Eco-OHPs. The most common reason for not purchasing was the lack of information about related brands or products (74, 56.5%). The most common platform used in obtaining information was the Internet (general: 31.5%, eco-friendly: 46.3%), such as Social Network Service, Internet cafes, and blogs. The experience in purchasing Eco-OHPs was affected by whether the respondents recognized the possibility of contributing to environmental preservation, availability of vendors, product safety, and the number of eco-friendly products purchased. Conclusion: In order to expand the use of Eco-OHPs, various efforts such as promotion of eco-friendly characteristics, determination of related vendors, reliable analysis of product safety, and expansion of product experience opportunities are required.

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.203-214
• /
• 2023

The Korea Customs Service is efficiently handling business with an electronic customs system that can effectively handle one-stop business. This is the case and a more effective method is needed. Import and export require HS Code (Harmonized System Code) for classification and tax rate application for all goods, and item classification that classifies the HS Code is a highly difficult task that requires specialized knowledge and experience and is an important part of customs clearance procedures. Therefore, this study uses various types of data information such as product name, product description, and product image in the item classification request form to learn and develop a deep learning model to reflect information well based on Multimodal representation learning. It is expected to reduce the burden of customs duties by classifying and recommending HS Codes and help with customs procedures by promptly classifying items.

• Informatization Policy
• /
• v.31 no.2
• /
• pp.105-132
• /
• 2024

This study seeks to investigate the factors influencing the utilization of online contents subscription services. In this study, the current number of online contents services subscribed to is set as the dependent variable. The independent variables include conspicuous product purchasing tendencies, personality types, experience with online contents consumption, and digital literacy. The research results indicate that digital literacy, agreeableness, and sociability among personality traits, as well as experience with online contents consumption, significantly impact the use of online contents subscription services. However, conspicuous product purchasing tendencies and personality traits such as openness and extroversion did not have a significant effect on the utilization of online contents subscription services.

• Journal of Internet Computing and Services
• /
• v.14 no.6
• /
• pp.95-105
• /
• 2013

Recently, SME's Collaboration activities have become one of a vital factor for sustaining competitive edge. This is because of the rapidly changing and competitive market environment, and also to leverage performance by overcoming obstacles of having limited internal resources. Discussing about the effects and relationships of the firm's collaboration activities and its outputs are not new. However, as ICT and various technologies have been diffused into the traditional industries, boundaries and practice capabilities within the industries are becoming ambiguous. Thus contents of the products/services and their development methods are also go and come over the industries. Although many researchers suggested the relations of SME's collaboration activities and innovation performances, most of the previous literatures are focusing on broad perspectives of firm's environmental factors rather than considering various SME's idiosyncrasy factors such as their major product and customer types at once. Therefore, the purpose of this paper is to analyze how SME(Small Medium Enterprise)'s external collaboration activities by their idiosyncrasy act as an input to types of innovation performance. In order to analyze collaboration effects in detail, we defined factors that can represent the SME's business environment - Perceived importance of using external resources, Perceived importance of external partnership, Collaboration and Collaboration levels of Major Product types, Customer types and lastly the Firm Sizes. We have also specifically divided the performance of innovation types as product innovation and process innovation based on existing research. In this study, the empirical analysis is based on Probit Regression Model to observe the correlations with the impact of each SME's business environment and their activities. For the empirical data, 497 samples were collected which, this sample data was extracted from the 'Korean Open Innovation Survey' performed by ETRI(Korean Electronics Telecommunications Research Institute) in 2010. As a result, empirical test results indicated that the impact of collaboration varies depend on the innovation types (Product and Process Innovation). The Impact of the collaboration level for the product innovation tend to be more effective when SMEs are developing for a final product, targeting on for individual customers (B2C). But on the other hand, the analysis result of the Process innovation tend to be higher than the product innovation, when SMEs are developing raw materials for their partners or to other firms targeting on for manufacturing industries(B2B). Also perceived importance of using external resources has effected to both product and process innovation performance. But Perceived importance of external partnership was statistically insignificant. Interesting finding was that the service product has negative effects on for the process innovation performance. And Relationship between size of the firms and their external collaboration activities with their performance of the innovations indicated that the bigger firms(over 100 of employees) tend to have better for both product and process innovations. Finally, implications of the results can be suggested as performance of innovation can be varied depends on firm's unique business idiosyncrasy as well as levels of external collaboration activities. The Implication of this research can be considered for firms in selecting an appropriate strategy as well as for policy makers.

• Asia pacific journal of information systems
• /
• v.18 no.1
• /
• pp.145-162
• /
• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.1-23
• /
• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Distribution Science
• /
• v.14 no.11
• /
• pp.139-147
• /
• 2016

Purpose - This study examines the effects of purchasing factors of consumers based on customer satisfaction and repurchasing intention buying through Internet shopping malls. The subject of this study are Chinese residents who have lived over a year in Korea. Research design, data, and methodology - In this study, former research related with internet shopping malls' customer satisfaction and repurchase intention was revised. Based on past research, the internet shopping mall purchasing factors divided to 4 factors; factors of product, price, service, and promotion. 5 hypotheses were made. They are

Product factors of internet shopping malls have meaningful effect to customer satisfaction,

Price factors of internet shopping malls have meaningful effect to customer satisfaction,

Service factors of internet shopping malls have meaningful effect to customer satisfaction,

Promotion factors of internet shopping malls have meaningful effect to customer satisfaction,

Customer satisfaction factors of internet shopping malls have meaningful effect to customer repurchase intention. Measurements developed 4~5 items to each factor and questionnaires were made. The survey was conducted on 1,000 Chinese people. Out of 292 surveys, 9 were excluded which responded nothing or were unfilled. Finally 283 surveys were used in empirical analysis with SPSS 22.0 statistical program. Hypotheses were verified by structural equation modeling. Results - The following conclusions are shown in the empirical study. First, the service and promotion factors of internet shopping mall have effects on customer satisfaction. Second, customer (Chinese people who live in Korea) satisfaction have effects on repurchase intention. Third, the products value and price level of internet shopping mall have strong effects on repurchasing intention. Conclusions - There are suggestions that Chinese customers satisfied with Korean internet shopping malls might increase their royalty to the shopping malls as possibility of repurchase arises. This study has differentiating points with preceding researches that subjected residents in Korea. But there are limitations that this study also used purchasing factors used in preceding studies. Also this study has limitations, such as generalization in global market circumstances because this study subjected only Chinese people and not global customers. Therefore, further study executed complementary with those limitations would be an interesting study.

• Journal of Korea Society of Industrial Information Systems
• /
• v.22 no.5
• /
• pp.101-111
• /
• 2017

This Research is to Find how the CSR Activities for the Growth of Stable and Sustainable Family Business do Influence the Improvement of Company's Brand Image and Service Purchase Intention. It is Aimed for Finding how the Image of Company Pursuing the Diverse CSR Activities is Recognized by General Consumers and the Correlation between the Improvement of Company's Image and the Product & Service Purchase Intention. 323 Exemplars were Distributed to the University Students in Seoul Metropolitan and Chungcheong Area, and 314 Finally were Used for the Analysis. It was Investigated the Demographical Factors, the Important Fields among Company's CSR Activities, the Reason for Company's CSR Activities, the Preferred Companies among Sponsoring Companies. It was Analyzed Three Items of Company Image such as Product/Service, Potential Competence, Relation to Public Benefit and the Regression Model was Investigated how these Three Items do Influence the Purchase Intention. The Research Results Show 'the Improvement of Social Awareness for Company' and 'Negative Awareness Change for Company' as the Reason for CSR. Consumers have the Preference to the Companies Actively Sponsoring Culture & Arts, and this Generally Affects the Business Results, and thus, it is Considered that the Companies have to Contribute the Local Society with the Sprit of Corporate Citizenship in Accordance with the Consumers needs, and Actively to Extend the Culture & Arts Sponsorship.

• Culinary science and hospitality research
• /
• v.22 no.4
• /
• pp.114-127
• /
• 2016

The study, focused on social commerce food service consumers, attempted to test the relationship between perceived risk and price consciousness, and suggested that perceived risk and price consciousness, the the degree to which price is considered when purchasing goods, affect reuse intention. Through such test results, the study aimed to provide useful practical implications for establishing marketing strategies of companies related to food service social commerce, and those looking into behavioral intentions of social commerce using food service consumers. The subjects of the study were male and female residents of Korea over 2-years of age who have had some experience purchasing a dining out item through social commerce. The social commerce company selected for sampling was Coupang, which was the number 1 shopping App in 2014 based on the number of yearly visitors. A questionnaire-based survey was conducted on respondents who had indicated that they had experience purchasing foodservice goods through Coupang. The results revealed that source risk, privacy risk, psychological risk, and time-loss risk had negative influences on reuse intention. However, social risk and financial risk did not exhibit any influences. Price consciousness had positive influences on reuse intention. The study explored perceived risk and price consciousness as elements to affect continuous use of social commerce of foodservice consumers.