• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.235-248
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• 2022

With the changes in the future educational environment, such as the rapid decline of the school-age population and the expansion of students' choice of curriculum, changes are also required in PCK, the expertise of science teachers. In other words, the categories constituting the existing 'consensus-PCK' and the characteristics of 'science PCK' are not fixed, so more categories and characteristics can be added. The purpose of this study is to explore the potential area of science PCK required to cope with changes in the future educational environment in the form of 'Family Resemblance Science PCK (Family Resemblance-PCK, hereafter)' through Wittgenstein's family resemblance approach. For this purpose, in-depth interviews were conducted with three focus groups. In the focus group in-depth interview, participants discussed how the science PCK required for science teachers in future schools in 2030-2045 will change due to changes in the future society and educational environment. Qualitative analysis was performed based on the in-depth interview, and semantic network analysis was performed on the in-depth interview text to analyze the characteristics of 'Family Resemblance-PCK' differentiated from the existing 'consensus-PCK'. In results, the characteristics of Family Resemblance-PCK, which are newly requested along with changes in role expectations of science teachers, were examined by PCK area. As a result of semantic network analysis of Family Resemblance-PCK, it was found that Family Resemblance-PCK expands its boundaries from the existing consensus-PCK, which is the starting point, and new PCK elements were added. Looking at the aspects of Family Resemblance-PCK, [AI-Convergence Knowledge-Contents-Digital], [Community-Network-Human Resources-Relationships], [Technology-Exploration-Virtual Reality-Research], [Self-Directed Learning-Collaboration-Community], etc., form a distinct network cluster, and it is expected that future science teacher expertise will be formed and strengthened around these PCK areas. Based on the research results, changes in the professionalism of science teachers in future schools and countermeasures were proposed as a conclusion.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.1-9
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• 2022

An estuary is an area where a freshwater river or stream meets the ocean. Even before the importance of the value of estuaries was recognized, the estuary was lost because of large-scale conversion by draining, filling, damming, and dredging. In South Korea, 643 estuaries are located, and the total area is 3,248,300 ha, accounting for 32.5% of the total area of South Korea. Over 35% of Korean estuaries are closed estuaries which are only temporally connected with the sea, either permanently or periodically. Since 2008, in order to preserve the estuary ecosystem and solve major issues in the estuary by accumulating knowledge about the estuarine ecosystem, the Ministry of Environment of Republic of Korea has been conducting the "Estuarine Ecosystem Monitoring and Assessment Project". At 668 sites of 325 estuaries, epilithic diatom, benthic macroinvertebrate, fish, and vegetation are investigated, and the habitat condition of each site is evaluated using the newly developed biotic index. More than 100 researchers annually record 2,097 species of estuaries according to the standardized survey guidelines over the past 14 years and provide strictly managed data necessary for establishing estuaries conservation policies. As a result of bibliometric analysis of 1,195 research articles related to the monitoring and assessment of the estuarine ecosystem, research on pollutants such as heavy metals and sediment control have recently been conducted. "Estuarine Ecosystem Monitoring and Assessment Project" is an ecological monitoring type of long-term mandated monitoring that is usually focused on identifying trends. Although it is difficult to identify the mechanism influencing a change in an ecosystem through long-term mandated monitoring, providing empirical data for supporting evidence-based policy, decision-making, and the management of ecosystems. In order to increase the efficiency of the project, research to investigate the relationship between sediments and pollutants and organisms can be conducted at specific estuaries or sites to compensate for the shortcomings of mandatory monitoring.

• Korea Science and Art Forum
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• v.29
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• pp.319-331
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• 2017

South Korea has entered the age of aging society since the elderly population over 65 reached 13.1% in 2015. This increase rate is the fastest in the OECD members. as a part of the precaution, the Korean government has enforced the long term care insurance from July 2008 and the increase of related nursing homes until 2015 was 220.2% which is rapid and quantitative. It was natural that quantitative expansion leads to qualitative improvement. With regard to service environment conditions, color environment draws attention as one of the most effective measures. color environment supports nursing home's spatial functions and the aged class is subject to the research as the potential customers. This study aims to understand color environment, conduct surveys for color preference and attitude toward color environment, and suggest directions for color environment plan. The ultimate goal is to improve the quality of Korean nursing home environment. It studied definition, state, color environment and space functions of nursing homes as well as the preceding researches. With 100 people over 60s in Busan and Gyeongnam area (52 male and 48 female), the survey examined attitudes for color environment and color preference by space functions in nursing home. The research method is as follows. First, as a result of the consciousness survey on color environment in elderly nursing home, it considers service (37%), medical service (20%), and location (19%) heavily in order. color environment plan is not recognized significantly. However, the need of indoor color plan in the elderly nursing homes has "agree (32%) and "strongly agree (25%), which suggests that color introduction is required to the nursing homes. Second, the indoor coloration for the elderly nursing homes has various color preferences. The color preference order for bedroom was R, P, and G but this order changes in nursing space (program room) to G, R, and Y. The communal space such as lobby prefers R, G and Y in order. R color was preferred in general.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.61-118
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• 2008

The purpose of this research is to construct research framework for international franchising based on existing literature and to identify research components in the framework. Franchise can be defined as management styles that allow franchisee use various management assets of franchisor in order to make or sell product or service. It can be divided into product distribution franchise that is designed to sell products and business format franchise that is designed for running it as business whatever its form is. International franchising can be defined as a way of internationalization of franchisor to foreign country by providing its business format or package to franchisee of host country. International franchising is growing fast for last four decades but academic research on this is quite limited. Especially in Korea, research about international franchising is carried out on by case study format with single case or empirical study format with survey based on domestic franchise theory. Therefore, this paper tries to review existing literature on international franchising research, providing research framework, and then stimulating new research on this field. International franchising research components include motives and environmental factors for decision of expanding to international franchising, entrance modes and development plan for international franchising, contracts and management strategy of international franchising, and various performance measures from different perspectives. First, motives of international franchising are fee collection from franchisee. Also it provides easier way to expanding to foreign country. The other motives including increase total sales volume, occupying better strategic position, getting quality resources, and improving efficiency. Environmental factors that facilitating international franchising encompasses economic condition, trend, and legal or political factors in host and/or home countries. In addition, control power and risk management capability of franchisor plays critical role in successful franchising contract. Final decision to enter foreign country via franchising is determined by numerous factors like history, size, growth, competitiveness, management system, bonding capability, industry characteristics of franchisor. After deciding to enter into foreign country, franchisor needs to set entrance modes of international franchising. Within contractual mode, there are master franchising and area developing franchising, licensing, direct franchising, and joint venture. Theories about entrance mode selection contain concepts of efficiency, knowledge-based approach, competence-based approach, agent theory, and governance cost. The next step after entrance decision is operation strategy. Operation strategy starts with selecting a target city and a target country for franchising. In order to finding, screening targets, franchisor needs to collect information about candidates. Critical information includes brand patent, commercial laws, regulations, market conditions, country risk, and industry analysis. After selecting a target city in target country, franchisor needs to select franchisee, in other word, partner. The first important criteria for selecting partners are financial credibility and capability, possession of real estate. And cultural similarity and knowledge about franchisor and/or home country are also recognized as critical criteria. The most important element in operating strategy is legal document between franchisor and franchisee with home and host countries. Terms and conditions in legal documents give objective information about characteristics of franchising agreement for academic research. Legal documents have definitions of terminology, territory and exclusivity, agreement of term, initial fee, continuing fees, clearing currency, and rights about sub-franchising. Also, legal documents could have terms about softer elements like training program and operation manual. And harder elements like law competent court and terms of expiration. Next element in operating strategy is about product and service. Especially for business format franchising, product/service deliverable, benefit communicators, system identifiers (architectural features), and format facilitators are listed for product/service strategic elements. Another important decision on product/service is standardization vs. customization. The rationale behind standardization is cost reduction, efficiency, consistency, image congruence, brand awareness, and competitiveness on price. Also standardization enables large scale R&D and innovative change in management style. Another element in operating strategy is control management. The simple way to control franchise contract is relying on legal terms, contractual control system. There are other control systems, administrative control system and ethical control system. Contractual control system is a coercive source of power, but franchisor usually doesn't want to use legal power since it doesn't help to build up positive relationship. Instead, self-regulation is widely used. Administrative control system uses control mechanism from ordinary work relationship. Its main component is supporting activities to franchisee and communication method. For example, franchisor provides advertising, training, manual, and delivery, then franchisee follows franchisor's direction. Another component is building franchisor's brand power. The last research element is performance factor of international franchising. Performance elements can be divided into franchisor's performance and franchisee's performance. The conceptual performance measures of franchisor are simple but not easy to obtain objectively. They are profit, sale, cost, experience, and brand power. The performance measures of franchisee are mostly about benefits of host country. They contain small business development, promotion of employment, introduction of new business model, and level up technology status. There are indirect benefits, like increase of tax, refinement of corporate citizenship, regional economic clustering, and improvement of international balance. In addition to those, host country gets socio-cultural change other than economic effects. It includes demographic change, social trend, customer value change, social communication, and social globalization. Sometimes it is called as westernization or McDonaldization of society. In addition, the paper reviews on theories that have been frequently applied to international franchising research, such as agent theory, resource-based view, transaction cost theory, organizational learning theory, and international expansion theories. Resource based theory is used in strategic decision based on resources, like decision about entrance and cooperation depending on resources of franchisee and franchisor. Transaction cost theory can be applied in determination of mutual trust or satisfaction of franchising players. Agent theory tries to explain strategic decision for reducing problem caused by utilizing agent, for example research on control system in franchising agreements. Organizational Learning theory is relatively new in franchising research. It assumes organization tries to maximize performance and learning of organization. In addition, Internalization theory advocates strategic decision of direct investment for removing inefficiency of market transaction and is applied in research on terms of contract. And oligopolistic competition theory is used to explain various entry modes for international expansion. Competency theory support strategic decision of utilizing key competitive advantage. Furthermore, research methodologies including qualitative and quantitative methodologies are suggested for more rigorous international franchising research. Quantitative research needs more real data other than survey data which is usually respondent's judgment. In order to verify theory more rigorously, research based on real data is essential. However, real quantitative data is quite hard to get. The qualitative research other than single case study is also highly recommended. Since international franchising has limited number of applications, scientific research based on grounded theory and ethnography study can be used. Scientific case study is differentiated with single case study on its data collection method and analysis method. The key concept is triangulation in measurement, logical coding and comparison. Finally, it provides overall research direction for international franchising after summarizing research trend in Korea. International franchising research in Korea has two different types, one is for studying Korean franchisor going overseas and the other is for Korean franchisee of foreign franchisor. Among research on Korean franchisor, two common patterns are observed. First of all, they usually deal with success story of one franchisor. The other common pattern is that they focus on same industry and country. Therefore, international franchise research needs to extend their focus to broader subjects with scientific research methodology as well as development of new theory.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.554-564
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• 2017

The purpose of this study is to assist farmers in determining the optimal time for the shipment of stored apples by investigating the market trends, storage status and release dates of low-temperature stored apples. We surveyed 300 apple cultivation farms in Daegu, Gyeongbuk Province, which is the main producer of apples, and examined the cultivars, cultivation areas, storage conditions, and shipment status of apples. The main results are as follows: the proportion of apples cultivatedat different ripening times was surveyed. According to the results, the proportions of early, middle and late varieties were 78.3%, 63.7% and 96.0%, respectively. Also, 48.7% of the farm households surveyed had cold storage facilities. The average storage cost per apple box(15kg) was 978.3 won for self-storage and 1,771.8 won for consignment storage. For the six(6) months between November and April, the proportion of shipped apples was 91.6% of the total stored apples. The (average total?)annual apple shipment, including apples stored in general storage warehouses, was 744.4 boxes. The (average total?) annual shipment of cold storage apples was 616 boxes. The stored apples were mainly shipped to 'wholesale markets', which have the highest sales share, followed by 'production site collectors' and then 'supermarkets'. The most common shipping method of the apples was by general trucks, followed by low-temperature trucks, and finally by delivery services. The analysis of the factors influencing the decision to release apples by period showed that it was affected by the storage cost, loss rate, and customary shipping in the off-season(from May to August). On the other hand, in the general release season(from November to April), the statistically significant decision factors for the release of apples were the future expected price, storage cost and decision of the leading farmer groups. For farmers with a high share of general shipment, the deciding factors for the release of apples were the future expected price, storage cost, high income expectation, and decision by leading farmers.

• Archives of design research
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• v.19 no.4 s.66
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• pp.133-144
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• 2006

According to the latest report by the Customer Protection Board, those who moved into newly constructed buildings are complaining about unidentified pains, asking for more careful selection of constructive materials for prevention of such potential problems. It is internationally recognized today that ecological materials can serve a significant factor for users' health, environmental protection and better industrial competitiveness. This study examined eco-design aspects of each interior material through web site search, in order to help customers learn about and capitalize on eco materials in a proper manner. As a result, 1. It turned out that the domestic industry are giving an impetus to releasing new eco items focusing on lower VOCs emission or addition of functional components as part of the marketing strategy. However, it is recommended that company understand significance of life cycle, and produce eco-concept materials. 2. The reliable standard for choosing the domestic material is EL, HB, GR marks. It is desirable to enhance recycling technologies and expand the sustainable consumption. customer class, since many recycled items are not developed. 3. The sourcing is a vulnerable part in terms of the concept of being environment-friendly material. Therefore, many manufacturers should design the easy knock-down products and produce the good items using recycled materials instead of new raw materials. Also solutions for making the energy from burning material should be studied. 4. The guidebook or manual with correct information about eco-materials is required to promote production and consumption with sustainable concept. 5. Many manufacturers are emphasizing ecological materials for customers, but some of them intended to disrupt customers' proper selection by promoting even unverified items to be environment-friendly.