• Asia pacific journal of information systems
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• 제19권2호
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• pp.117-137
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• 2009

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 distance-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 programming. 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.

• Asia pacific journal of information systems
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• 제19권2호
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• pp.139-155
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• 2009

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 evaluation 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 boundaries, 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 bankruptcy, 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.

• Asia pacific journal of information systems
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• 제19권2호
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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 information systems
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• 제19권2호
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• pp.1-42
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• 2009

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 behavioral 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 communities 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 communication 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-person 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 management 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 relationships, 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 environments, thereby resulting in positive outcomes for both individuals and organizations. In addition, the information 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) significantly 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.

• Asia pacific journal of information systems
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• 제19권2호
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• pp.195-221
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• 2009

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 measurement 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 finding. 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 communication among members within an organization. Accordingly, we conclude that the higher the task dependency, 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 between 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 antecedent 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.

• Asia pacific journal of information systems
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• 제19권2호
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• pp.43-72
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• 2009

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 involvement of the 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 characteristic 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 communication paradigm created by UCC.

• Asia pacific journal of information systems
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• 제23권3호
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• pp.131-154
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• 2013

New internet technologies have created a revolutionary new platform which allows consumers to make decision about product price and quality quickly and provides information about themselves through the transcript of online reviews. By expressing their feelings toward products or services on virtual opinion platforms, users extend their influence into cyberspace as electronic word-of-mouth (e-WOM). Existing research indicates that an impact of eWOM on the consumer decision process is influential. For both academic researchers and practitioners, investigating this phenomenon of information sharing in online website is essential given the increasing number of consumers using them as sources of purchase decisions. It is worthwhile to examine the extent to which opinion seekers are willing to accept and adopt online reviews and which factors encourage adoption. Discerning the most motivating aspects of information adoption in particular, could help electronic marketers better promote their brand and presence on the internet. The objectives of this study are to investigate how online WOM influences a persons' purchase decision by discovering which factors encourage information adoption. Especially focused on the self-efficacy, this research investigates how self-efficacy affects on information usefulness and adoption of online information. Although people are exposed to same review or comment about product or service, some accept the reviews while others do not. We notice that accepting online reviews mainly depends on the person's preference or personal characteristics. This study empirically examines this issue by using cognitive dissonance theory. Specifically, in the movie industry, we address few questions-is always positive WOM generating positive effect? What if the movie isn't the person's favorite genre? What if the person who is very self-assertive so doesn't take other's opinion easily? In these cases of cognitive dissonance, is always WOM generating same result? While many studies have focused on one direct of WOM which indicates positive (or negative) informative reviews or comments generate positive (or negative) results and more (or less) profits, this study investigates not only directional properties of WOM but also how people change their opinion towards product or service positive to negative, negative to positive through the online WOM. An experiment was conducted quantitatively by using a sample of 168 users who have experience within the online movie review site, 'Naver Movie'. Users were required to complete a survey regarding reviews and comments taken from the real movie page. The data reflected user's perceptions of online WOM information that determined users' adoption level. Analysis results provide empirical support for the proposed theoretical perspective. When user can't agree with the opinion of online WOM information, in other words, when cognitive dissonance between online WOM information and users' preference occurs, perceived self-efficacy significantly decreases customers' perception of usefulness. And this perception of usefulness plays an important role in determining users' intention to adopt online WOM information. Most of researches have been concentrated on characteristics of online WOM itself such as quality or vividness of information, credibility of source and direction of online WOM, etc. for describing effect of online WOM, but our results suggest that users' personal character (e.g., self-efficacy) plays decisive role for acceptance of online WOM information. Higher self-efficacy means lower possibility to accept the information that represents counter opinion because of cognitive dissonance, whereas the people that have lower self-efficacy are willing to accept the online WOM information as true and refer to purchase decision. This study suggests a model for understanding role of direction of online WOM information. Also, our result implicates the importance of online review supervision and personalized information service by confirming switching opinion negative to positive is more difficult than positive to negative through the online WOM information. This implication would help marketers to manage online reviews of their products or services.

• Asia pacific journal of information systems
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• 제23권3호
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• pp.1-23
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• 2013

Open Source Software Development (OSSD) differentiates itself from traditional closed software development in that it reveals its source codes online and allows anyone to participate in projects. Even though its success was in doubt, many of the open collaborative working models produced successful results. Academia started to get interested in how developers are willing to participate even when there are no extrinsic rewards for their efforts. Many studies tried to explain developers' motivations, and the pursuit of ideology, reputation, and altruism are found to be the answers. Those studies, however, focused mostly on how the first contribution is made out of a certain motivation. Nowadays, OSSD reaches at its maturity and 70% of professional developers have used or utilized open source software or code in their works. As the proportion of people experiencing OSS, the accounts from previous studies are expected to be weakened. Also, extant literature fails to explain how the motivation of participating in OSS evolves over time and experiences. Given that changing over time or over experiences is the natural in the perception of motivation, studies in an attempt to understand how the motivation changes or evolves are in need. In this study, we aimed to explain how the perception about OSS from past usage or related experiences leads to the intention to sustain OSS participations. By doing so, we try to bridge the gap between previous studies and the actual phenomenon. We argued that perceived instrumentality about OSS learned from past experiences will first affect the formation of organizational identity towards general OSS community. And once the organizational identity is formed, it will affect the one's following behaviors related to OSS development, most likely to sustain the favoring stance toward OSS community. Our research distinguishes itself from previous one in that it divides the paths from organizational identity formed to the intention to sustain the voluntary helping behaviors, by altruistic and conforming intentions. Drawing on this structural model, we could explain how organizational identity engages in forming the sustaining intention from past experiences, and that the intention to help at individual level and organizational level works at different level in OSS community. We grounded our arguments on Social identity theory and Organizational Citizenship theory. We examined our assumption by constructing a structural equation model (SEM) and had 88 developers to answer our online surveys. The result is analyzed by PLS (partial least square) method. Consequently, all paths but one in our model are supported, the one which assumed the association between perceived instrumentality and altruistic intention. Our results provide directions in designing online collaborative platforms where open access collaboration is meant to occur. Theoretically, our study suggests that organizational citizenship behavior can occur from organizational identity, even in bottom-up organizational settings. More specifically, we also argue to consider both organizational level and individual level of motivation in inducing sustained participations within the platforms. Our result can be interpreted to indicate the importance of forming organizational identity in sustaining the participatory behaviors. It is because there was no direct association between perceived instrumentality from past experiences and altruistic behavior, but the perception of organizational identity bridges the two constructs. This means that people with no organizational identity can sustain their participations through conforming intention from only the perception of instrumentality, but it needs little more than that for the people to feel the intention to directly help someone in the community-first to form the self-identity as a member of the given community.

• 한국산림과학회지
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• 제83권3호
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• pp.365-371
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• 1994

본 연구는 우리나라에 자생하는 주목(Taxus cuspidata S. et Z.), 설악눈주목(Taxus caepiltosa Nakai)과 회솔나무(Taxus cuspidata var. latifolia Nakai)에서 탁솔을 추출하고 정량하여 자생지별, 채취부위별 탁솔함량의 차이를 조사하기 위하여 수행되었다. 주목은 한라산, 지리산, 덕유산, 소백산, 태백산에서, 설악눈주목은 설악산에서 10월에 수피, 줄기, 그리고 잎을 채취하였으며, 회솔나무는 울릉도에서 3월에 줄기와 잎을 채취하였다. 채취한 재료는 HPLC(High Performance Liquid Chromatography)로 정량분석하고 분석한 자료를 통계처리하여 각 집단간의 차이를 검정하였다. 주목의 경우 채취부위별 탁솔함량은 수피에서 평균 0.006~0.017%로 가장 높았고 줄기에서는 0.001~0.005%이었고, 잎에서 0.0005~0.002%로 가장 낮았다. 수피의 탁솔함량은 한라산에서 가장 높은 0.017%이었으며, 지리산, 소백산, 덕유산, 태백산의 순으로 감소하였다. 줄기의 탁솔함량은 한라산에서 가장 높은 0.0053%이었으며, 소백산, 지리산, 덕유산, 태백산의 순으로 감소하였다. 잎의 탁솔함량은 한라산에서 가장 높은 0.0013%이었으며, 태백산, 덕유산과 지리산의 순으로 감소하였다. 설악눈주목에서의 탁솔함량은 주목보다 낮았으며, 수피와 줄기에서 평균 0.0035%이었다. 회솔나무에서의 탁솔함량은 줄기에서는 주목보다 높았으나, 줄기에서 평균 0.0064%, 잎에서 0.0006%이었다. 위와 같은 결과를 종합하여 보면, 탁솔의 함량은 위도가 낮아질수록 높아지는 경향을 보이고 있으며, 생육조건에 따라서 큰 변이가 있는 것으로 관찰되었다. 한라산 집단의 일부 주목(Taxus cuspidata)은 높은 탁솔함량을 나타내었으며, 이를 설발육종하거나, 조직배양을 통하여 상업용 탁솔생산이 가능하다고 생각된다.

• 벤처창업연구
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• 제10권5호
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• pp.73-81
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• 2015

본 연구는 벤처중소기업의 조직여유와 개방형 경영혁신 간의 관계에서 사회적 자본의 조절효과를 분석하기 위한 실증분석 연구이다. 즉 기업규모, 기업연령, 환경 불확실성을 통제한 뒤, 다음의 두 가지 가설을 검증하였다. 첫 번째 가설은 벤처중소기업의 조직여유(흡수된 여유, 흡수되지 않은 여유)가 개방형 경영혁신에 유의한 긍정적인 영향을 미치는 지 여부이다. 두 번째 가설은 벤처중소기업의 조직여유(흡수된 여유, 흡수되지 않은 여유)와 개방형 경영혁신 간의 관계에서 사회적 자본이 긍정적인 조절역할을 수행하는 지 여부이다. 이와 같은 가설을 검증하기 위해 설문지법을 사용하여 유효한 250개의 기업수준 데이터를 확보하였다. 또한 실증분석은 SPSS 18.0을 통해 빈도분석, 타당도분석, 신뢰도분석, 상관분석, 회귀분석을 실시하였다. 이러한 실증분석 결과, 두 가지 의미 있는 결과를 도출하였다. 첫째, 벤처중소기업의 조직여유 유형 중 현금, 유가증권 등과 같은 흡수되지 않은 여유는 개방형 경영혁신에 유의한 정(+)의 영향을 미쳤으나, 초과인력, 초과설비 등과 같은 흡수된 여유는 개방형 경영혁신에 유의한 영향을 미치지 않았다. 이는 흡수되지 않은 여유가 흡수된 여유에 비해 유연하고 활동적이어서 개방형 혁신에 긍정적인 영향을 미칠 수 있음을 의미한다. 둘째, 벤처중소기업에서의 사회적 자본은 유연하게 활용 가능한 흡수되지 않은 여유와 개방형 경영혁신 간의 관계를 긍정적으로 조절하는 반면, 이미 조직에 흡수되어 버린 흡수된 여유와 개방형 경영혁신 간의 관계는 조절하지 못함이 나타났다. 이 연구 결과는 사회적 자본과 개방형 혁신 간의 관계를 연구한 기존 선행연구가 거의 없기에 더욱 의미를 가질 것으로 기대된다.