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In an attempt to cope with widespread, dynamic, and accelerating changes in both internal and external business environments, companies often utilize information technologies such as SCM(Supply Chain Management). To date, SCM research has mainly focused on the effects of dynamic factors on SCM success and emphasized adoption strategies and critical success factors. Consequently, the effects of more static factors such as interdependency between SCM partners have been largely ignored. The purpose of this study, therefore, is to examine the effects of both dynamic and static factors on SCM performance by controlling for information quality and partnership quality. The five factors examined in this study include innovativeness, mutual dependency, quality of information, partnership quality, and SCM performance. All factors were examined from the perspective of part suppliers, except the mutual dependency which was examined from two aspects: supplier's dependency on customer and customer's dependency on supplier. Data was collected through five hundred survey questionnaires distributed to the part supplier companies that have implemented SCM systems for at least one year. As a result, a total of 170 valid responses were obtained. A structural equation research model was fitted using SAS 9.1.3 and SMART-PLS 2.0. The results of this study can be summarized as follows. First, innovativeness positively affected SCM information quality, SCM partnership quality, and ultimately SCM performance. The path coefficient between innovativeness and information quality was 0.387, with a t-value of 3.528. Innovativeness also had a positively direct effect on partnership quality. The path coefficient was 0.351 with a t-value of 3.366. The total effect of innovativeness on partnership quality was significant, although its indirect effect on partnership quality by altering information quality was negligible. The total indirect effect of innovativeness on SCM performance by affecting information quality and partnership quality was significant with a p-value of 0.014. Innovativeness played an important role in determining SCM performance. Second, mutual dependency showed no significant effect on SCM information quality. This result contradicts the earlier assertion that the more dependent two companies are, the more accurate and timely the information they exchange ought to be. This study showed that this may not be the case; a partner may provide information of poor quality even when it is strongly dependent on the other. Mutual dependency showed significant effect on partnership quality. However, when the mutual dependency perceived by suppliers was divided into two parts, one being a supplier's dependency on its customer company and the other being a customer's dependency on the supplier, the latter showed a significant impact on the perceived SCM partnership quality. This result indicates that a customer company can hardly improve the partnership quality perceived by suppliers by making them more dependent. It improves only when the suppliers perceive that their partners, typically having more bargaining power, are more dependent on them. The overall effect of mutual dependency of any kind on SCM performance, however, was not significant. Although mutual dependency has been mentioned as an important static factor influencing almost every aspect of cooperation on a supply chain, its influences may not be as significant as it was initially perceived to be. Third, the correlation between information quality and partnership quality was 0.448 with a p-value of less than 0.001. Information quality had a path coefficient of 0.256 to partnership quality with a t-value of 2.940. The quality of information exchanged between partners may have an impact on their partnership quality. Fourth, information quality also had a significant impact on SCM performance with a path coefficient of 0.325 with a t-value of 3.611. In this study, SCM performance was divided into four categories: product quality, cost saving, service quality, and order fulfillment. Information quality has significant impacts on product quality, cost saving and service quality, but not on order fulfillment. Fifth, partnership quality, as expected, had a significant impact on SCM performance. The path coefficient was 0.403 with a t-value of 3.539. Partnership quality, like information quality, had positive impacts on product quality, cost saving and service quality, but showed no impact on order fulfillment. It seemed that order fulfillment is the hardest category of performance that SCM can satisfy. One major limitation of this study is that it surveyed only the suppliers. To better understand the dual aspects of SCM, it is important to survey both suppliers and the assemblers, especially in pairs. This research, to our best knowledge, was the first attempt to study the level of dependency between the two groups by measuring the dual aspects of SCM and studying mutual dependency from the categories of suppliers and assemblers each.. In the future, a more comprehensive and precise measurement of SCM characteristics needs to be achieved by examining from both the supplier's and assembler's perspectives.

Despite the growing attention to the effective utilization of ICT system in workplace, there is an accumulation of evidence from the literature indicating that organizations do not utilize newly introduced ICT systems to their full functional potential and an amount of new implementations continue to fail. We explore the reasons for the underutilization of new ICT by focusing on the individuals’ social networks. This paper investigates how the social networks influence individual adaptation to the new ICT and its related performance. Based on the coping theory, we establish a research model that explains the coping mechanism. Collected data are analyzed to test the proposed model and its hypotheses using PLS and UCINET. The results show that the coping effort mechanism of individuals can be explained in terms of their positions within social networks. We conclude the paper by discussing theoretical and practical implications for the research findings and by proposing future studies.

E-government needs to be successfully implemented and assimilated into organizations to take advantage of its potential values and benefits for organizations. This study examines factors for e-government assimilation in Indonesia and employs the TOE (Technology-Organization-Environment) framework to develop a theoretical model to explain e-government assimilation. It also investigates how organizational type (central vs. local) plays a role in the assimilation of e-government. One hundred eighteen respondents from the central and local governments in Indonesia participated in the survey and an in-depth analysis based on partial least squares (PLS) was carried out. The results show that ICT infrastructure has the strongest significant relationship with e-government assimilation. Top management support, regulatory environment, ICT expertise, and competitive environment are also significant factors to explain e-government assimilation in Indonesia. Central and local governments significantly differ in terms of e-government assimilation, so organizational type can be a moderator in the process of e-government assimilation. These findings present the efficacy of the proposed model for analyzing e-government assimilation and contribute additional insights for academia as well as practitioners and policy makers.

In today’s rapidly changing and increasingly competitive business environment, new product development in tune with market trends in a timely manner has been a matter of the utmost concern for all enterprises. Indeed, developing a sustainable new business has been a top priority for not only business enterprises, but also for the government policy makers accountable for the health of its national economy as well as for decision makers in what type of organizations. Further, for a soft landing of new businesses, building a government-initiated industry base has been claimed to be necessary as a way to effectively boost corporate activities. However, the existing methodology in new service and new product development is not suitable for nurturing industry, because it is mainly focused on the research and development of corporate business activities instead of new product development. The approach for developing new business is based on ‘innovation’ and ‘convergence.’ Yet, the convergence among technologies, supplies, businesses and industries is believed to be more effective than innovation alone as a way to gain momentum. Therefore, it has become more important than ever to study a new methodology based on convergence in industrial quality new product development (NPD) and new service development (NDS). In this research, therefore, we reviewed any restrictions in the existing new product and new service development methodology and the existing business model development methodology. In doing so, we conducted industry standard collaboration analysis on a new service model development methodology in the private sector and the public sector. This approach is fundamentally different from the existing one in that ours focuses on new business development under private management. The suggested framework can be categorized into industry level and service level. First, in the industry level, we define new business opportunities in occurrence of convergence between businesses. For this, we analyze the existing industry at the industry level to identify the opportunities in a market and its business attractiveness, based on which the convergence industry is formulated. Also, through the analysis of environment and market opportunity at the industry level, we can trace how different industries are lined to one another so as to extend the result of the study to develop better insights into industry expansion and new industry emergence. After then, in the service level, we elicit the service for the defined new business, which is composed of private service and supporting service for nurturing industry. Private service includes 3steps: plan-design-do; supporting service for nurturing industry has 4 steps: selection-make environment- business preparation-do and see. The existing methodology focuses on mainly securing business competitiveness, building a business model for success, and offering new services based on the core competence of companies. This suggested methodology, on other hand, suggests the necessity of service development, when new business opportunities arise, in relation to the opportunity analysis of supporting service based on the clear understanding of new business supporting infrastructure optimization. Meanwhile, we have performed case studies on the printing and publishing field with the restrict procedure and development system to assure the feasibility and practical application. Even though the printing and publishing industry is considered a typical knowledge convergence industry, it is also known as a low-demand and low-value industry in Korea. For this reason, we apply the new methodology and suggest the direction and the possibility of how the printing and publishing industry can be trnasformed as a core dynamic force for new growth. Then, we suggest the base composition service for industry promotion(public) and business opportunities for private’s profitability(private).

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document, and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment, namely IVSM (Inverse Vector Space Model). The model is based on a vector space model, which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.