• Asia pacific journal of information systems
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• v.24 no.2
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• pp.191-210
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• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.11
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• pp.545-561
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• 2007

Location management and message delivery protocol is fundamental to the further development of mobile agent systems in a multi-region mobile agent computing environment in order to control mobile agents and guarantee message delivery between them. However, previous works have some problems when they are applied to a multi-region mobile agent computing environment. First, the cost of location management and message delivery is increased relatively. Second, a tracking problem arises. finally, cloned mobile agents and parent-child mobile agents do not get dealt with respect to location management and message delivery. In this paper, we present a HB (Home-Blackboard) protocol, which is a new location management and message delivery protocol in a multi-region mobile agent computing environment. The HB protocol places a region server in each region and manages the location of mobile agents by using intra-region migration and inter-region migration. It also places a blackboard in each region server and delivers messages to mobile agents when a region server receives location update form them. The HB protocol can decrease the cost of location update and message passing and solve the tracking problem with low communication cost. Also, this protocol deals with the location management and message passing of cloned mobile agents and parent-child mobile agents, so that it can guarantee message delivery of these mobile agents and pass messages without passing duplicate messages.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.37-57
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• 2018

With the spread of smart phones, interest in mobile media is on the increase as useful media recently. Mobile media is assessed as having differentiated advantages from existing media in that not only can they provide consumers with desired information anytime and anywhere but also real-time interaction is possible in them. So far, studies on mobile advertising were mostly researches analyzing satisfaction with, and acceptance of, mobile advertising based on survey, researches focusing on the factors affecting acceptance of mobile advertising messages and researches verifying the effect of mobile advertising on brand recall, advertising attitude and brand attitude through experiments. Most of the domestic mobile advertising studies related to advertisement effect and advertisement attitude have been conducted through experiments and surveys. The advertising effectiveness measure of the mobile ad used the attitude of the advertisement, purchase intention, etc. To date, there have been few studies on the effects of mobile advertising on actual advertising data to prove the characteristics of the advertising platform and to prove the relationship between the factors influencing the advertising effect and the factors. In order to explore advertising effect of mobile advertising platform currently commercialized, this study defined advertising characteristics and media characteristics from the perspective of advertiser, advertising platform and publisher and analyzed the influence of each characteristic on advertising effect. As the advertisement characteristics, we classified advertisement format classified by bar type and floating type, and advertisement material classified by image and text. We defined advertisement characteristics of advertisement platform as Hedonic and Utilitarian media characteristics. As a dependent variable, we use CTR, which is the ratio of response (click) to ad exposure. The theoretical background and the analysis of the mobile advertising business, the hypothesis that the advertisement effect is different according to the advertisement specification, the advertisement material, In the ad standard, bar ads are classified as static framing, Floating ads can be categorized as dynamic framing, and the hypothetical definition of floating advertisements, which are high-profile dynamic framing ads, is highly responsive. In advertising, images with high salience are defined to have higher ad response than text. In the media characteristics classified as practical / hedonic type, it is defined that the hedonic type media has a more relaxed tendency than the practical media, and there is a high possibility of receiving various information because there is no clear target. In addition, image material and hedonic media are defined to be highly effective in the interaction between advertisement specification and advertisement material, advertisement specifications and media characteristics, and advertisement material and media characteristics. As the result of regression analysis on each characteristic, material standard, which is a characteristic of mobile advertisement, and media characteristics separated into 'Hedonic' and 'Utilitarian' had significant influence on advertisement effect and mutual interaction effect was also confirmed. In the mobile advertising standard, the advertising effect of the floating advertisement is higher than that of the bar advertisement, Floating ads were more effective than text ads for image ads. In addition, it was confirmed that the advertising effect is higher in the practical media than the hedonic media. The research was carried out with the big data collected from the mobile advertising platform, and it was possible to grasp the advertising effect of the measure index standard which is used in the practical work which could not be grasped in the previous research. In other words, the study was conducted using the CTR, which is a measure of the effectiveness of the advertisement used in the online advertisement and the mobile advertisement, which are not dependent on the attitude of the ad, the attitude of the brand, and the purchase intention. This study suggests that CTR is used as a dependent variable of advertising effect based on actual data of mobile ad platform accumulated over a long period of time. The results of this study is expected to contribute to establishment of optimum advertisement strategy such as creation of advertising materials and planning of media which suit advertised products at the time of mobile advertisement.

• Information Systems Review
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• v.14 no.3
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• pp.53-74
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• 2012

IT outsourcing (ITO) is an integration of two firms-external vendor(s) and a client firm-IT resources by contract. According to resource-based view(RBV), three different resources-ITO vendor's resource, client firm's resource, and the relationship resource between two firms- may have an impact on ITO performance. However, there have been few previous studies considering all three IT resources simultaneously. There have been also few empirical studies in ITO context, which test Bharadwaj (2000)'s findings: 1) IT resources can be divided into tangible IT asset and intangible IT capability, and 2) only IT capability has an impact on the IT performance. Therefore we examined whether, in ITO context, all three different resources have a significant impact on ITO performance. Adopting the findings of previous IT studies, we also divided IT resource into IT asset and IT capability. To achieve this research objective, we analyzed 62 ITO cases of 45 companies being listed in Korean top 100 companies for recent 3 years. Also, we analyzed the data with the Partial Least Squares method. The results of this research lead to the following conclusions: First, only when partnership is high, ITO vendors' resource can have an influence on ITO performance. Second, only client firm's IT capability, not IT asset, is directly related to the ITO success. Third, a firm's IT capability can increase the partnership. Therefore, we concluded that 1) RBV is also an useful theory in ITO context, 2) Bharadwaj(2000)'s suggestion is valid in ITO context as well, and 3) the relationship resource is also important in ITO.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.115-137
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• 2010

Information technology (IT) outsourcing, the use of a third-party vendor to provide IT services, started in the late 1980s and early 1990s in Korea, and has increased rapidly since 2000. Recently, firms have increased their efforts to capture greater value from IT outsourcing. To date, there have been a large number of studies on IT outsourcing. Most prior studies on IT outsourcing have focused on outsourcing practices and decisions, and little attention has been paid to objectively measuring the value of IT outsourcing. In addition, studies that examined the performance of IT outsourcing have mainly relied on anecdotal evidence or practitioners' perceptions. Our study examines the contribution of IT outsourcing to economic growth in Korean industries over the 1990 to 2007 period, using a production function framework and a panel data set for 54 industries constructed from input-output tables, fixed-capital formation tables, and employment tables. Based on the framework and estimation procedures that Han, Kauffman and Nault (2010) used to examine the economic impact of IT outsourcing in U.S. industries, we evaluate the impact of IT outsourcing on output and productivity in Korean industries. Because IT outsourcing started to grow at a significantly more rapid pace in 2000, we compare the impact of IT outsourcing in pre- and post-2000 periods. Our industry-level panel data cover a large proportion of Korean economy-54 out of 58 Korean industries. This allows us greater opportunity to assess the impacts of IT outsourcing on objective performance measures, such as output and productivity. Using IT outsourcing and IT capital as our primary independent variables, we employ an extended Cobb-Douglas production function in which both variables are treated as factor inputs. We also derive and estimate a labor productivity equation to assess the impact of our IT variables on labor productivity. We use data from seven years (1990, 1993, 2000, 2003, 2005, 2006, and 2007) for which both input-output tables and fixed-capital formation tables are available. Combining the input-output tables and fixed-capital formation tables resulted in 54 industries. IT outsourcing is measured as the value of computer-related services purchased by each industry in a given year. All the variables have been converted to 2000 Korean Won using GDP deflators. To calculate labor hours, we use the average work hours for each sector provided by the OECD. To effectively control for heteroskedasticity and autocorrelation present in our dataset, we use the feasible generalized least squares (FGLS) procedures. Because the AR1 process may be industry-specific (i.e., panel-specific), we consider both common AR1 and panel-specific AR1 (PSAR1) processes in our estimations. We also include year dummies to control for year-specific effects common across industries, and sector dummies (as defined in the GDP deflator) to control for time-invariant sector-specific effects. Based on the full sample of 378 observations, we find that a 1% increase in IT outsourcing is associated with a 0.012~0.014% increase in gross output and a 1% increase in IT capital is associated with a 0.024~0.027% increase in gross output. To compare the contribution of IT outsourcing relative to that of IT capital, we examined gross marginal product (GMP). The average GMP of IT outsourcing was 6.423, which is substantially greater than that of IT capital at 2.093. This indicates that on average if an industry invests KRW 1 millon, it can increase its output by KRW 6.4 million. In terms of the contribution to labor productivity, we find that a 1% increase in IT outsourcing is associated with a 0.009~0.01% increase in labor productivity while a 1% increase in IT capital is associated with a 0.024~0.025% increase in labor productivity. Overall, our results indicate that IT outsourcing has made positive and economically meaningful contributions to output and productivity in Korean industries over the 1990 to 2007 period. The average GMP of IT outsourcing we report about Korean industries is 1.44 times greater than that in U.S. industries reported in Han et al. (2010). Further, we find that the contribution of IT outsourcing has been significantly greater in the 2000~2007 period during which the growth of IT outsourcing accelerated. Our study provides implication for policymakers and managers. First, our results suggest that Korean industries can capture further benefits by increasing investments in IT outsourcing. Second, our analyses and results provide a basis for managers to assess the impact of investments in IT outsourcing and IT capital in an objective and quantitative manner. Building on our study, future research should examine the impact of IT outsourcing at a more detailed industry level and the firm level.

• Management & Information Systems Review
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• v.23
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• pp.41-74
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• 2007

In Korea, corporate merger activities were activated since 1980, and nowadays(particuarly since 1986) the changes in domestic and international economic circumstances have made corporate managers have strong interests in merger. Korea and America have different business environments and it is easily conceivable that there exists many differences in motives, methods, and effects of mergers between the two countries. According to recent studies on takeover bids in America, takeover bids have information effects, tax implications, and co-insurance effects, and the form of payment(cash versus securities), the relative size of target and bidder, the leverage effect, Tobin's q, number of bidders(single versus multiple bidder), the time period (before 1968, 1968-1980, 1981 and later), and the target firm reaction (hostile versus friendly) are important determinants of the magnitude of takeover gains and their distribution between targets and bidders at the announcement of takeover bids. This study examines the theory of takeover bids, the status quo and problems of merger in Korea, and then investigates how the announcement of merger are reflected in common stock returns of bidding firms, finally explores empirically the factors influencing abnormal returns of bidding firms' stock price. The hypotheses of this study are as follows ; Shareholders of bidding firms benefit from mergers. And common stock returns of bidding firms at the announcement of takeover bids, shows significant differences according to the condition of the ratio of target size relative to bidding firm, whether the target being a member of the conglomerate to which bidding firm belongs, whether the target being a listed company, the time period(before 1986, 1986, and later), the number of bidding firm's stock in exchange for a stock of the target, whether the merger being a horizontal and vertical merger or a conglomerate merger, and the ratios of debt to equity capital of target and bidding firm. The data analyzed in this study were drawn from public announcements of proposals to acquire a target firm by means of merger. The sample contains all bidding firms which were listed in the stock market and also engaged in successful mergers in the period 1980 through 1992 for which there are daily stock returns. A merger bid was considered successful if it resulted in a completed merger and the target firm disappeared as a separate entity. The final sample contains 113 acquiring firms. The research hypotheses examined in this study are tested by applying an event-type methodology similar to that described in Dodd and Warner. The ordinary-least-squares coefficients of the market-model regression were estimated over the period t=-135 to t=-16 relative to the date of the proposal's initial announcement, t=0. Daily abnormal common stock returns were calculated for each firm i over the interval t=-15 to t=+15. A daily average abnormal return(AR) for each day t was computed. Average cumulative abnormal returns($CART_{T_1,T_2}$) were also derived by summing the $AR_t's$ over various intervals. The expected values of $AR_t$ and $CART_{T_1,T_2}$ are zero in the absence of abnormal performance. The test statistics of $AR_t$ and $CAR_{T_1,T_2}$ are based on the average standardized abnormal return($ASAR_t$) and the average standardized cumulative abnormal return ($ASCAR_{T_1,T_2}$), respectively. Assuming that the individual abnormal returns are normal and independent across t and across securities, the statistics $Z_t$ and $Z_{T_1,T_2}$ which follow a unit-normal distribution(Dodd and Warner), are used to test the hypotheses that the average standardized abnormal returns and the average cumulative standardized abnormal returns equal zero.

• Asia pacific journal of information systems
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• v.19 no.2
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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.

• Journal of the Korean Chemical Society
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• v.8 no.1
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• pp.20-24
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• 1964

The linear combination of bond orbitals method is used to investigate the reactivity of halomethanes in abstraction reactions by atoms. The activation energy is evaluated on the assumption that, in an activated complex, two electrons in a bond to be broken become completely isolated from the rest of the ${\sigma}$-electron systems. Such a model leads to an intuitively attractive concept that the interactions between the reactive bond and the neighboring bonds govern the reactivity of ${\sigma}$-electron systems. The resulting equation for the activation energy, ${\varepsilon},\;is:\;{\narepsilon}= ${\varepsilon}={\zeta}+$$${\sum}_{i=1}^3$${\eta}c-I,$ c-4 Here, subscript C-4 indicates the bond to be broken, while C-i represents the other three bonds surrounding the reactive bond; ξ is the activation energy of a hypothetical reaction of an isolated C-4 bond and an attacking atom; and ${\eta}$C-i,C-4 stems from the stabilizing interacting of C-4 bond with neighboring C-i bonds. A choie of η′s consistent with bond strength data simplifies the above equation to a form ${\varepsilon}={\zeta}\;+\;N{\eta}c$-H, C-4 where N denotes the number of C-H plus C-F bond in halomethanes. In agreement with this equation, experimental -values increase linearly with increasing N.

• Management & Information Systems Review
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• v.36 no.3
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• pp.219-237
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• 2017

Looking into the top-five innovative sectors in Korea's manufacturing and service industries, this study empirically analyzes the effect of innovation performance on R&D investment, which is one of the most important strategic decisions for corporate management. In the midst of an uncertain business environment, R&D investment has been regarded as the most important strategic decision making in corporate management related to innovation. Corporate management, however, tend to be reluctant to make sufficient R&D investment due to the risk of an investment failure. Therefore, having R&D investment by offsetting this risk has been deemed as a key task for corporate management. However, prior studies have failed to identify which factors affect companies' strategic decision making on R&D investment. This study is to remedy this weakness of prior study. Relying on path dependency theory at organization-level and dominant logic at individual-level, this study empirically examines the multiple regression model, which sees entrepreneurial orientation as a positive mediator between innovation performance and R&D investment. The results found in the analysis of 242 local companies in the manufacturing and service sectors represent that innovation performance has a direct and positive effect on R&D investment, while it indirectly affects R&D investment through the mediating roles of entrepreneurial orientation. They also revealed that innovation performance had a meaningful impact on entrepreneurial orientation, which is an inclination to seek innovation, led to R&D investment. The founding of this study imply that innovation performance in the past affects innovation strategies in the future, and such a relationship could be strengthened by entrepreneurial orientation as the dominant logic of corporate management.

• Journal of the Korean Geographical Society
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• v.29 no.2
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• pp.117-136
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• 1994

Contemporary global space economy is so dynamic that any one specific structural force can not explain the whole dynamic processes or trajectories of spatial industrial development. The major purpose of this paper is extending the traditional notion of industrial districts to functioning and development of new industrial districts with relation to the development of high technology industries. Several dynamic forces, which are dominated in new industrial districts in the modern space economy, are incorporated in the formation and dynamic aspects of new industrial districts. Even though key forces governing Marshallian industrial district are localization of small firms, division of labor between firms, constructive cooperation, and industrial atmosphere, Marshall points out a possibility of growing importance of large firms and non-local networks in the districts with changes of external environments. Some of Italian industrial districts can be regarded as Marshallian industrial districts in broader context, but the role of local authorities or institutions and local embeddedness seem to be more important in the Italian industrial districts. More critical implication form the review of Marshallian industrial districts and Italian industrial districts is that the industrial districts are not a static concept but a dynamic one: small firm based industrial districts can be regarded as only a specific feature evolved over time. Dynamic aspects of new industrial districts are resulting from coexistence of contrasting forces governing the functioning and formation of the districts in contemporary global space economy. The contrasting forces governing new industrial districts are coexistence of flexible and mass production systems, local and global networks, local and non-local embeddedness, and small and large firms. Because of these coexistence of contrasting forces, there are various types of new industrial districts. Nine types of industrial districts are identified based on local/non-local networks and intensity of networks in both suppliers and customers linkages. The different types of new industrial districts are described by differences in production systems, embeddedness, governance, cooperation and competition, and institutional factors. Out of nine types of industrial districts, four types - Marshallian; suppliers hub and spoke; customers hub and spoke; and satellite - are regarded as distinctive new industrial districts and four additional types - advanced hub and spoke types (suppliers and customers) and mature satellites (suppliers and customers) - can be evolved from the distinctive types and may be regarded as hybrid types. The last one - pioneering high technology industrial district - can be developed from the advanced hub and spoke types and this type is a most advanced modern industrial district in the era of globalization and high technology. The dynamic aspects of the districts are related with the coexistence of the contrasting forces in the contemporary global space economy. However, the development trajectory is not a natural one and not all the industrial districts can develop to the other hybrid types. Traditionally, localization of industries was developed by historical chances. In the process of high technology industrial development in contemporary global space economy, however, policy and strategies are critical for the formation and evolution of new industrial districts. It needs formation of supportive tissues of institutions for evolution of dyamic pattern of high technology related new industrial districts. Some of the original distinctive types of new industrial districts can not follow the path or trajectory suggested in this paper and may be declined without advancing, if there is no formation of supportive social structure or policy. Provision of information infrastructure and diffusion of an entrepreneurship through the positive supports of local government, public institutions, universities, trade associations and industry associations are important for the evolution of the dynamic new industrial districts. Reduction of sunk costs through the supports for training and retraining of skilled labor, the formation of flexible labor markets, and the establishment of cheap and available telecommunication networks is also regarded as a significant strategies for dynamic progress of new industrial districts in the era of high technology industrial development. In addition, development of intensive international networks in production, technology and information is important policy issue for formation and evolution of the new industrial districts which are related with high technology industrial development.