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In a knowledge-based society, a firm’s intellectual capital represents the wealth of ideas and ability to innovate, which are indispensable elements for the future growth. Therefore, the intellectual capital is evidently recognized as the most valuable asset in the organization. Considered as intangible asset, intellectual capital is the basis based on which firms can foster their sustainable competitive advantage. One of the essential components of the intellectual capital is a social capital, indicating the firm’s individual members’ ability to build a firm’s social networks. As such, social capital is a powerful concept necessary for understanding the emergence, growth, and functioning of network linkages. The more social capital a firm is equipped with, the more successfully it can establish new social networks. By providing a shared context for social interactions, social capital facilitates the creation of new linkages in the organizational setting.This concept of “person-environment fit” has long been prevalent in the management literature. The fit is grounded in the interaction theory of behavior. The interaction perspective has a fairly long theoretical tradition, beginning with proposition that behavior is a function of the person and environment. This view asserts that neither personal characteristics nor the situation alone adequately explains the variance in behav-ioral and attitudinal variables. Instead, the interaction of personal and situational variables accounts for the greatest variance. Accordingly, the person-environment fit is defined as the degree of congruence or match between personal and situational variables in producing significant selected outcomes.In addition, information systems acceptance factors enable organizations to build large electronic commun-ities with huge knowledge resources. For example, the Intranet helps to build knowledge-based communities, which in turn increases employee communication and collaboration. It is vital since through active communica-tion and collaborative efforts can employees build common basis for shared understandings that evolve into stronger relationships embedded with trust. To this aim, the electronic communication network allows the formation of social network to be more viable to rapid mobilization and assimilation of knowledge assets in the organizations.The purpose of this study is to investigate: (1) the impact of person-environment fit(person-job fit, person-per-son fit, person-group fit, person-organization fit) on social capital(network ties, trust, norm, shared language); (2) the impact of information systems acceptance factors(availability, perceived usefulness, perceived ease of use) on social capital; (3) the impact of social capital on personal performance(work performance, work satisfaction); and (4) the mediating role of social capital between person-environment fit and personal performance. In general, social capital is defined as the aggregated actual or collective potential resources which lead to the possession of a durable network. The concept of social capital was originally developed by sociologists for their analysis in social context. Recently, it has become an increasingly popular jargon used in the manage-ment literature in describing organizational phenomena outside the realm of transaction costs. Since both environmental factors and information systems acceptance factors affect the network of employee's relation-ships, this study proposes that these two factors have significant influence on the social capital of employees. The person-environment fit basically refers to the alignment between characteristics of people and their envi-ronments, thereby resulting in positive outcomes for both individuals and organizations. In addition, the in-formation systems acceptance factors have rather direct influences on the social network of employees.Based on such theoretical framework, namely person-environment fit and social capital theory, we develop our research model and hypotheses. The results of data analysis, based on 458 employee cases are as follow: Firstly, both person-environment fit(person-job fit, person-person fit, person-group fit, person-organization fit) and information systems acceptance factors(availability·perceived usefulness, perceived ease of use) sig-nificantly influence social capital(network ties, norm, shared language). In addition, person-environment fit is a stronger factor influencing social capital than information systems acceptance factors. Secondly, social capital is a significant factor in both work satisfaction and work performance. Finally, social capital partly plays a mediating role between person-environment fit and personal performance.Our findings suggest that it is vital for firms to understand the importance of environmental factors affecting social capital of employees and accordingly identify the importance of information systems acceptance factors in building formal and informal relationships of employees. Firms also need to reflect their recognition of the importance of social capital’s mediating role in boosting personal performance. Some limitations arisen in the course of the research and suggestions for future research directions are also discussed.

Recently, user-created content (UCC) have emerged as popular medium of on-line participation among users. The Internet environment has been constantly evolving, attracting active participation and information sharing among common users. This tendency is a significant deviation from the earlier Internet use as an one-way information channel through which users passively received information or contents from contents providers. Thanks to UCCs online users can now more freely generate and exchange contents; therefore, identifying the critical factors that affect content-generating activities has increasingly become an important issue. This paper proposes a set of critical factors for stimulating contents generation and sharing activities by Internet users. These factors were derived from the theories of folklores such as tales and songs. Based on some shared traits of folklores and UCC content, we found four critical elements which should be heeded in constructing UCC contents, which are: context of culture, context of situation, skill of generator, and response of audience. In addition, we selected three major UCC websites: a specialized contents portal, a general internet portal, and an official contents service site. They have different use environments, user interfaces, and service policies. To identify critical factors for generating, sharing and transferring UCC, we traced user activities, interactions and flows of content in the three UCC websites. Moreover, we conducted extensive interviews with users and operators as well as policy makers in each site.Based on qualitative and quantitative analyses of the data, this research identifies nine critical factors that facilitate contents generation and sharing activities among users. In the context of culture, we suggest voluntary community norms, proactive use of copyrights, strong user relationships, and a fair monetary reward system as critical elements in facilitating the process of contents generation and sharing activities. Norms which were established by users themselves regulate user behavior and influence content format. Strong relationships of users stimulate content generation activities by enhancing collaborative content generation. Particularly, users generate contents through collaboration with others, based on their enhanced relationship and specialized skills. They send and receive contents by leaving messages on website or blogs, using instant messenger or SMS. It is an interesting and important phenomenon, because the quality of contents can be constantly improved and revised, depending on the specialized abilities of those engaged in a particular content. In this process, the reward system is an essential driving factor. Yet, monetary reward should be considered only after some fair criterion is established. In terms of the context of the situation, the quality of contents uploading system was proposed to have strong influence on the content generating activities. Among other influential factors on contents generation activities are generators’ specialized skills and involve-ment of other users were proposed. In addition, the audience response, especially effective development of shared interests as well as feedback, was suggested to have significant influence on contents generation activities. Content generators usually reflect the shared interest of others. Shared interest is a distinct character-istic of UCC and observed in all the three websites, in which common interest is formed by the “threads” embedded with content. Through such threads of information and contents users discuss and share ideas while continuously extending and updating shared contents in the process. Evidently, UCC is a new paradigm representing the next generation of the Internet. In order to fully utilize this innovative paradigm, we need to understand how users take advantage of this medium in generating contents, and what affects their content generation activities. Based on these findings, UCC service providers should design their websites as common playground where users freely interact and share their common interests. As such this paper makes an important first step to gaining better understand about this new communi-cation paradigm created by UCC.

The general aspects for the future warfare shows that the concept of firepower and maneuver centric warfare has been replacing with that of information and knowledge centric warfare. Thus, some developed countries are now trying to establish the information systems to perform intelligent warfare and innovate defense operations.The C4I(Command, Control, Communication, Computers and Intelligence for the Warrior) systems make it possible to do modern and systematic war operations. The basic idea of this study is to investigate how TAM(Technology Acceptance Model) can explain the acceptance behavior in military organizations. Because TAM is inadequate in explaining the acceptance processes forcomplex technologies and strict organizations, a revised research model based upon TAM was developed in order to assess the usage of the C4I system.The purpose of this study is to investigate factors affecting the usage of C4I in the Korean Army. The research model, based upon TAM, was extended through a belief construct such as self-efficacy as one of mediating variables. The self-efficacy has been used as a mediating variable for technology acceptance, and the variable was included in the research model. The external variables were selected on the basis of previous research. The external variables can be classified into following: 1) technological, 2) organizational, and 3) environmental factors on the basis of TOE(Technology-Organization-Environment) framework. The tech-nological factor includes the information quality and the task-technology fitness. The organizational factor includes the influence of senior colleagues. The environmental factor includes the education/train data. The external variables are considered very important for explaining the behavior patterns of information technology or systems.A structured questionnaire was developed and administrated to those who were using the C4I system. Total 329 data were used for statistical data analyses. A confirmatory factor analysis and structured equation model were used as main statistical methods. Model fitness indexes for measurement and structured models were verified before all 18 hypotheses were tested.This study shows that the perceived usefulness and the self-efficacy played their roles more than the per-ceived ease of use did in TAM. In military organizations, the perceived usefulness showed its mediating effects between external variables and dependent variable, but the perceived ease of use did not. These results imply that the perceived usefulness can explain the acceptance processes better than the perceived ease of use in the army. The self -efficacy was also used as one of the three mediating variables, and showed its mediating effects in explaining the acceptance processes. Such results also show that the self-efficacy can be selected as one possible belief construct in TAM.The perceived usefulness was influenced by such factors as senior colleagues, the information quality, and the task-technology fitness. The self-efficacy was affected by education/train and task-technology fitness. The actual usage of C4I was influenced not by the perceived ease of use but by the perceived usefulness and selfefficacy. This study suggests the followings: (1) An extended TAM can be applied to such strict organizations as the army; (2) Three mediation variables are included in the research model and tested at real situations; and (3) Several other implications are discussed.

Increasingly the institutional theory has been an important theoretical view of decision making process and IT adoption in many academic researches. This study used the institutional theory as a lens through which we can understand the factors that enable the effective appropriation of advanced information technology. It posits that mimetic, coercive, and normative pressures existing in an institutionalized environment could influence the participation of top managers or decision makers and the involvement of users toward an effective use of IT in their tasks. Since the introduction of IT, organizational members have been using IT in their daily tasks, creating and recreating rules and resources according to their own methods and needs. That is to say, the adaptation process of the IT and outcomes are different among organizations. The previous studies on a diverse use of IT refer to the appropriation of technology from the social technology view. Users appropriate IT through not only technology itself, but also in terms of how they use it or how they make the social practice in their use of it. In this study, the concepts of institutional pressure, appropriation, participation of decision makers, and involvement of users toward the appropriation are explored in the context of the appropriation of the mobile electronic medical record system (M-EMRS) in particularly a hospital setting. Based on the conceptual definition of institutional pressure, participation and involvement, operational measures are reconstructed. Furthermore, the concept of appropriation is measured in the aspect of three sub-constructs-consensus on appropriation, faithful appropriation, and attitude of use.Grounded in the relevant theories to appropriation of IT, we developed a research framework in which the effects of institutional pressure, participation and involvement on the appropriation of IT are analyzed. Within this theoretical framework, we formulated several hypotheses. We developed a second order institutional pressure and appropriation construct. A fter establishing its validity and reliability, we tested the hypotheses with empirical data from 101 users in 3 hospitals which had adopted and used the M-EMRS. We examined the mediating effect of the participation of decision makers and the involvement of users on the appropriation and empirically validated their relationships.The results show that the mimetic, coercive, and normative institutional pressure has an effect on the participation of decision makers and the involvement of users in the appropriation of IT while the participation of decision makers and the involvement of users have an effect on the appropriation of IT. The results also suggest that the institutional pressure and the participation of decision makers influence the involvement of users toward an appropriation of IT.Our results emphasize the mediating effect of the institutional pressure on the appropriation of IT. Namely, the higher degree of the participation of decision makers and the involvement of users, the more effective appropriation users will represent. These results provide strong support for institutional-based variables as pre-dictors of appropriation. These findings also indicate that organizations should focus on the role of participation of decision makers and the involvement of users for the purpose of effective appropriation, and these are the practical implications of our study. The theoretical contribution of this study is lies in the integrated model of the effect of institutional pressure on the appropriation of IT. The results are consistent with the institutional theory and support previous studies on adaptive structuration theory.

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task.However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data.This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle’s velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used dis-tance-based shortest path.A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle’s velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle’s velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic pro-gramming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking.In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs.For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

For the last few decades, many studies have tried to explore and unveil venture companies’ success factors and unique features in order to identify the sources of such companies’ competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors’ attention. Investors generally make their investment decisions by carefully examining the evalua-tion criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor’s, Moody’s and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm’s efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies.First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings.The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik [1995]. As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business. SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class bounda-ries, we can transform the inputs into a high-dimensional feature space. This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bank-ruptcy, the forecast a financial time series, and the problem of estimating credit rating. In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins[1999] and Crammer and Singer[2000], respectively.In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies’ financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples.We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

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 be-cause 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 techni-ques 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 applyMSVMs to credit ratings studies..In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-All, (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.

As the common saying attests, a publish-or-perish world, publishing is absolutely critical for academic re-searchers' successful careers. It is the most objectively-accepted academic performance criteria and the most viable way to attain public and academic recognition.Asia Pacific Journal of Information Systems(APJIS) has been recognized as the most influential domestic journal in Korean MIS field since July, 1991. Therefore, publishing in APJIS means your research is original, valid, and contributive. While most researchers learn how to publish an article in APJIS through a repetitive review process, thereby improving their chance of the 'accepted' through their personal trial and error experi-ences, such valuable lessons and know-how tend to be kept personally and rarely shared. However, useful insights into research and publication skills could be also gained from sharing others’ errors, neglect, and misjudgments which are equally critical in improving researchers’ knowledge in the field (Murthy and Wiggins, 2002). For this reason, other academic disciplines make systematic efforts to examine the paper review process of major journals and share the findings from these studies with the rest of the research community members (Beyer et al., 1995; Cummings et al, 1985; Daft, 1995; Jauch and Wall, 1989; Murthy and Wiggins, 2002). Recognizing the urgent need to provide such type of information to MIS research community in Korea, we have chosen the most influential academic journal, APJIS with an intention to share the answer to the following research question: "What are the common problems found in the manuscripts either 'rejected' or 'required a major revision' by APJIS reviewers?"This study analyzes the review results of manuscripts submitted to APJIS (from January, 2006 to October, 2008), particularly those that were ‘rejected’ or required a ‘major revision’ at the first round. Based on Daft's(1995) study, twelve most-likelihood problems were defined and used to analyze the reviews. The twelve criteria for classification, or "twelve problems", are as follows: No theory, Concepts and operationalization not in alignment, Insufficient definition--theory, Insufficient rationale--design, Macrostructure--organization and flow, Amateur style and tone, Inadequate research design, Not relevant to the field, Overengineering, Conclusions not in alignment, Cutting up the data, and Poor editorial practice.Upon the approval of the editorial board of APJIS, the total 252 reviews, including 11 cases of 2005 and 241 cases from July, 2006 to October, 2008, were received without any information about manuscripts, authors, or reviewers. Eleven cases of 2005 were used in the pilot test because the data of 2005 were not in complete enumeration, and the 241 reviews (113 cases of 'rejection' and 128 ones of 'major revision') of 2006, 2007, and 2008 were examined in this study.Our findings show that insufficient rationale--design(20.25%), no theory(18.45%), and insufficient defi-nition--theory(15.69%) were the three leading reasons of 'rejection' and 'major revision.' Between these two results, the former followed the same order of three major reasons as an overall analysis (insufficient ration-ale--design, no theory, and insufficient definition--theory), but the latter followed the order of insufficient ration-ale--design, insufficient definition--theory, and no theory.Using Daft's three major skills-- 'theory skills', 'design skills', and 'communication skills'-- twelve criteria were reclassified into 'theory problems', 'design problems', and 'communication problems' to derive more practical implications of our findings. Our findings show that 'theory problems' occupied 43.48%, 'design prob-lems' were 30.86%, and 'communication problems' were 25.86%. In general, the APJIS reviewers weigh each of these three problem areas almost equally. Comparing to other disciplines like management field shown in Daft's study, the portion of 'design problems' and 'communication problems' are much higher in manuscripts submitted to the APJIS than in those of Administrative Science Quarterly and Academy of Management Journal even though 'theory problems' are the most predominant in both disciplines.

According to an industry report, a large number of organizations have invested in Organizational Information System(OIS) in the past few years. Several research results indicate that successful investments in OIS lead to productivity enhancement, while failed ones result in undesirable consequences such as financial losses and dissatisfaction among employees. In spite of huge investments, however, many organizations have failed in achieving the hoped-for returns from OIS. Thus, understanding user acceptance, adoption, and usage of new IS(Information Systems) is an important issue for IS practitioners.Indeed, study of the user acceptance of new information system has been one of the most important research topics in the contemporary IS literature. Several theoretical models are tested to examine 'user acceptance' and 'usage behavior' in IS context. While many research models incorporate 'ease of use' or 'usefulness' as important factors in explaining user acceptance, Technology Acceptance Model(TAM) has been one of the most widely applied models in user acceptance and usage behavior. Even in recent IS studies that employ theories of innovation diffusion in the area of IS implementation, a major focus has been on the user's perception of information technologies. In this research, we study 'voluntariness' as an important factor in IS acceptance by users. Voluntariness is defined as "the degree to which the use of the innovation is perceived as being voluntary, or of free will" When examining the diffusion of accepting OIS, a thoughtful consideration should be given to 'perceived voluntariness.' Current article has following research questions: 1) What models are appropriate to explain the success of OIS? and 2) How does the 'voluntariness' affect the success of OIS? In order to answer these questions, a research model is proposed to describe the detailed nature of association among three independent variables (IT usage level, task interdependency, and organizational support), a mediating variable (IS usage), a dependent variable (perceived performance), and a moderating variable(perceived voluntariness). The central claim of this article is that organizations hardly realize expected returns from OIS investments unless perceived voluntariness is effectively managed after operating OIS.As an example of OIS in this study we have selected the Intranet of Republic of Korea Air Force (ROKAF). ROKAF has implemented the Intranet in an attempt to improve communication and coordination within the organization. To test our research model and hypotheses, survey questionnaires were first sent out to 400 Intranet users. With the assistance of ROKAF, Intranet users were initially identified among its members, and subjects were randomly drawn from the pool. 377 survey responses were finally returned. The unit of measure-ment and analysis in this research is a personal level.Path analysis based on structural equation modeling was used to test research hypotheses. Construct validity represents accordance between the theoretical base concept of constructs and its measurement items. Tests for the reliability and discriminant validity are accepted, thus verifying our survey instrument. In this research, we have proposed a conceptual framework to highlight the importance of perceived voluntariness after organization deploys OIS. The results of our analysis present several key findings. First, all three independent variables (IT usage level, task interdependency, and organizational support) have significant effects on IS usage, which will eventually improve performance. Thus, IS usage plays a mediating role between antecedent variables (IT usage level, task interdependency, and organizational support) and performance improvement. Second, the effect of the task dependency was the highest for IS usage among the three antecedent variables. This is highly plausible since one of the Intranet's major capabilities is to facilitate commu-nication among members within an organization. Accordingly, we conclude that the higher the task depend-ency, the higher Intranet usage. The effect of user's IT usage level was the second, while the effect of the organizational support was the third. Finally, the perceived voluntariness plays a pivotal role in enhancing perceived performance in personal level after launching the Intranet. Relationships among investigated variables were significantly different be-tween groups with a high level and a low level of voluntariness. The impact of the Intranet usage on the performance was greater in the higher level voluntariness group than in the lower one. For the lower level voluntariness group, the user's IT usage had the highest effect on the Intranet usage among the three ante-cedent variables. In short, our study suggests that the higher the perceived voluntariness is the more IS usage will be. Perceived voluntariness was found to have a moderating effect on the relationships among user IT usage level, task interdependency, IS usage, and perceived performance, supporting all the hypotheses on the moderating effect. Most of all, user IT usage level has the strongest influence on IS usage, indicating that users with superior IT usage are more likely to enjoy a high level of perceived performance.