• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.6
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• pp.11-26
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• 2016

Businesses have to survive and thrive in both domestic and international environments. In order to resolve these problems, new alternatives have been presented. These include the importance of women's resources and entrepreneurship of female CEOs. The sensibility, delicacy, creativity as well as the intuitive power of female CEOs, actively enables them to cope with the ever-changing environment. Because of the rapidly changing circumstances, the above mentions women's attributes are highlighted thus, causing women's roles in society to shift from their traditional tendencies to finding careers and their own identities. Due to this change in social roles, social interest and the values of female CEOs are being reevaluated. Accordingly, the conceptual consideration of female entrepreneurship (innovation, enterprise, risk sensitivity) as well as the factors to be considered for the entrepreneurship of female CEOs in order to promote knowledge management performance was derived in this research. The deducted implication of this research is that generally, the enterprise and risk sensitivity of entrepreneurship affect the knowledge management performance of female CEOs. It is therefore proved that in the case of female CEOs, entrepreneurship and self-efficacy are linked, allowing them to achieve the desired outcome for a specific task performance. Female CEOs are capable of company management through the mediating process of their enterprise, risk sensitivity, and self-efficacy and with faith in their knowledge management, will be able to achieve high performance. Therefore, using strengths and nature peculiar to women, women's economic activities derived from knowledge management based on entrepreneurship will not only help overcome the long-term economy crisis but also lead to high economic growth and development. This will be a dynamic force for the nation's new growth with financial means. The comparative study of existing results will also contribute in suggesting the direction of policies that will enable the success of female CEOs in entrepreneurship.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.1-15
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• 2023

Impact investment involves investing in companies that pursue both social value and financial returns. It focuses on addressing various social problems through innovative solutions while generating profits. The domestic impact investment ecosystem has experienced significant growth with the support of the government and public institutions. In 2021, it witnessed a 3.5-fold increase over three years, reaching a total of 700 billion won in operating assets. In order to foster qualitative growth alongside this quantitative expansion, it is crucial to conduct research specifically on impact investment, which sets it apart from conventional venture investment. This study aims to empirically analyze the unique factors that influence impact investment decisions. Firstly, the factors affecting investment decisions were identified through a literature analysis. Then, a consultation and Delphi survey involving 11 representatives and evaluators from impact investment companies was conducted to determine the major investment determinants. Subsequently, an AHP (Analytic Hierarchy Process) survey was carried out with 10 impact investment evaluators to ascertain the relative importance of these factors. The analysis revealed the following order of importance for the top factors: market>entrepreneur(team)>product/service>finance. Furthermore, the importance of specific factors was identified in the following order: market competition and entry barriers>new market creation>market growth and potential expansion>team expertise and capabilities. Unlike previous studies that primarily focus on general startup investment factors, this research demonstrates that impact investment places greater emphasis on market-related factors and considers the sustainability and profitability of the business model to be more important than the social impact of social ventures.

• Journal of Navigation and Port Research
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• v.28 no.1
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• pp.59-67
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• 2004

As the environment for international logistics varies according to the globalization in world economy, world-class seaports are struggling for the position as strongholds in their own block. As a new government begins its own era in Korea, they are positively implementing their strategies at the level of government for making the Korean Peninsula the logistics centre in North-eastern Asia, marking the most of its geographic advantage. As one of those strategies, it plans to foster a specific area as an international logistics base camp in Northeast Asia by activating its logistics industry through inducing multinational logistics enterprises. In reality, however, in order for Busan seaport, the late-comer, to induce investment from the world-class multinational companies, a considerably large volume of investment should be given from both central and local governments. Accordingly, the objective of this study is to assess its competitiveness and to suggest an activation plan for BSDFA(Busan Seaport Duty-Free Area), based upon the results of on-the-spot interviews in China and Japan. The survey for the respondent's preference by way of Conjoint Analysis indicated that Investment procedures and limitations get the highest 36.2％ preference, so the most critical strategy to be considered for attracting enterprises into DFA(Duty-Free Area) is to solve the problems related to the investment procedures and limitations. The simulation analysis results for market share showed that UAE has the highest preference and BSDFA the lowest preference among the five countries. However, when the levels of investment procedures and limitations and production costare upgraded, the competitiveness of BSDFA was elevated next to that of UAE among the 5 countries. Thus, in order for BSDFA to obtain competitiveness, it is implied that production cost level as well as investment procedures and limitations level, should be lowered so that it could meet companies' demand.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.1
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• pp.1-28
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• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and Empirical Research on the R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research. Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.3
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• pp.109-129
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• 2011

Since the introduction of local autonomy system, various specific theories and practical approaches for private commission system have been common concerns and interests of the fields practicing social welfare. In the discussion about private consignment system of social welfare facility and organization, both of private section and government have shown different opinions from various aspects such as related regulation, consignment procedure, proper period and consignment condition. According to the discussion about the consignment system of social welfare facility, the purpose of this study is as follows. The first purpose is to suggest the current status of private consignment of social welfare facility and the characteristic and issue of consignment procedure by considering domestic & overseas literatures about the characteristic of private consignment system. The second purpose is to find out the general characteristics and current statuses of consignment process and system of social welfare facilities (organizations) located in Gyeonggi-do area. The third purpose is to draw the current status and general problem of field consignment system and suggest the practical alternative plan and improvement method of private consignment system of social welfare facility in the future. The result of researching private consignment process by head and manager of social welfare facility (organization), private consignment agreement and its conclusion process and current consignment system improvement method revealed that the number of reconsigned (over 1~3 times) facilities was more than that of initially consigned facilities and senior welfare facility and general social welfare center were most frequent in private consignment organization. In addition, as an improvement method of current private consignment process, the consideration on each organization and standard was required for new consignment and reconsignment and the problem of fairness and objectiveness was indicated when deliberation committee was organized in private consignment process. Besides them, it was found that consignment period shall be adjusted on the basis of facility type and business characteristic and the problems such as worker's succession, worker's transfer and service disconnection were suggested when consignment organization was changed. For conclusion and suggestion, the study suggested the establishment of common standard about private consignment, alternative plan of private consignment process issue and improvement method of consignment period issue.

• International Commerce and Information Review
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• v.15 no.1
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• pp.35-65
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• 2013

In December 2012, the Ministry of Land, Transport and Maritime Affairs and Ministry of Knowledge Economy held a commission and distributed a standardized logistics contract between the shipper and the logistics companies in order to spread and to promote contract standardization. With such background in place, this study examines the leading research on different types and attributions in present logistics contracts in order to propose guidelines for creating contract clauses that would lead to a win-win relationship among the parties involved in the logistics outsourcing relationships. This study further compares and contrasts the concreteness of local and international logistics contracts through case studies, and provides practical thought-provoking points on concretization of clauses on potential risks and additional expenses for local logistics companies when signing logistics contracts. Firstly, the composition and contents of both local and international logistics contracts are similar in the way that both deal with the basic principles between the concerned parties such as the following: contract terms, validity, scope of work, operational procedures, payment terms, and dispute resolutions. Secondly, for flexibility of potential dispute resolution, both logistics contracts define the definition of dispute and follow the classical contractual approach of dispute resolution through third-party arbitration. Thirdly, compared to local contracts, international logistics contracts provide more concretized and specific clauses on the occurrence of potential risks and hazards; on the other hand, compared to international logistics contracts, it seemed that local contracts contained more clauses in favor of the shipper. This research then suggests ideas to eliminate the classic tradition - logistics companies enduring the damages that occur as a result of the structural differences between the shipper and the logistics companies - through efforts to actively negotiate in advance the predictable problems and risks and by reflecting the mutually agreed points in the contract, and further offers guidelines on contract concretization for distribution of standardized logistics contracts in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.1-16
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• 2022

Although start-up is a key national strategy to increase national competitiveness and create employment, the survival rate of start-ups has not improved significantly. This is an important reason for the inability to provide timely and appropriate support to startups, which are in the early stages of start-up, due to the unique limitations of existing start-up support institutions and investors. The relatively recent accelerator is attracting attention as a subject of solving the above problems through professional incubation and investment. However, there are only a few empirical studies on investment determinants that affect the survival and success of accelerators, and there is a lack of theoretical evidence. Accordingly, in previous studies, 12 investment determinants were derived from a static, strategic, and dynamic perspective as accelerator investment determinants based on a business model innovation framework. This study subdivided the accelerator investment determinants derived through previous studies into 21 and analyzed the importance and priority of each factor using AHP (Analytic Hierarchy Process) analysis technique for domestic accelerator investment experts. As a result of the analysis, the top factors of importance of accelerator investment determinants were in the order of 'human resources', 'customer and market', 'intellectual resources', and 'entrepreneur's ability to realize opportunities'. It can be seen that the accelerator considers the core competencies of startups to implement solutions as the most important factor when making startup investment decisions. It was also confirmed that accelerators are strategic to create a clear value proposition and differentiated market position based on the core competitiveness of startups, and that the core value delivery method prefers a market-oriented business model and recognizes entrepreneurs's innovation capability is an important factor to realize a business model with limited resources in a rapidly changing market. This study is of academic significance in that it analyzes the importance and priority of accelerator investment determinants through demonstration as a follow-up study on accelerator investment determinants derived based on business model innovation theory that reflects the nature, goals, and major activities of accelerator investment. In addition, it is of practical value as it contributes to revitalizing the domestic startup investment ecosystem by providing accelerators with theoretical grounds for investment decisions and specific information on detailed investment determinants.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.