• Journal of Korean Society of Archives and Records Management
• /
• v.22 no.3
• /
• pp.55-81
• /
• 2022

The purpose of this study is to explore a budget-securing strategy to enable archival professionals in public institutions to continuously secure the budget for records management projects. This study is an analysis of the results of in-depth interviews with 14 archival professionals who have worked for public institutions and secured budgets for records management projects. As a result of the analysis, 4 upper categories and 10 categories are extracted as factors influencing budget securement. The top four categories are the job environment of archival professionals, umbrella organization and organizational culture, business and budget characteristics, and system and social environment. As the budget-securing strategy for archival professionals, a total of 3 categories and 13 strategic codes are derived. The three categories are utilizing individual-centered competencies, establishing organization-centered relationships, and finding external environment-centered triggers. This study emphasized the perspective of archival professionals and suggested implications such as the role of archival professionals and the direction of improvement in securing budgets.

• Asia-Pacific Journal of Business
• /
• v.14 no.2
• /
• pp.85-100
• /
• 2023

Purpose - The purpose of this study is to identify the factors of shocking events in the career aspect experienced by Korean workers in the context of the Covid-19 pandemic, and to find out whether these career shocks affect individual perceptions of the importance of subjective career success. Design/methodology/approach - In the survey of 146 respondents, the career shock events experienced in the context of the Covid-19 pandemic were largely divided into three categories; 'work change', 'employment anxiety', and 'life anxiety'. For the subjective career success, seven dimensions - 'financial security', 'financial achievement', 'entrepreneurship', 'positive relationship', 'positive impact', 'learning and development', 'work-life balance' - were used. Findings - As a result, there was no difference in the perception of subjective career success due to the experience of 'work change' during the Covid-19 period. However, the respondents who experienced 'employment anxiety' came to recognize that 'financial security' and 'financial achievement' were more increasing in terms of the degree of difference of importance. And respondents who experienced 'lifetime anxiety' perceived that the degree of difference of importance was increasing in the six dimensions except for 'social influence'. Particularly, the increase in the importance of 'work-life balance' and 'positive relationship' was found to be the greatest among the career success dimensions. Research implications or Originality - Finally, it was concluded that changes in the external environment such as Covid-19 pandemic influence as a career shock and affect the level of importance in subjective career success perception. Based on the results, the theoretical implication on current career study and some practical implications for organizational career management were suggested.

• Journal of Korea Technology Innovation Society
• /
• v.18 no.1
• /
• pp.28-48
• /
• 2015

This study is public R & D institutions report to verify what the impact factors on the course of progress of industrialization based on technology companies who previously received prior to the developed technology, what policies and plans for the next requirements based on this by offering the implications for business rate was to contribute to the improvement of the public research institution technology transfer. In this study, the influence factors on technology commercialization derived through the analysis of existing and previous studies, the characteristics of the previously received corporate environmental characteristics and previous technologies through a survey of the company received a technology transfer from public research institutions commercialization decisions and contributions, including sales and commercialization of the results were analyzed by logistic regression analysis demonstrated how to have relevance. Analysis, and linkage with high production company has an existing case of IT technology transfer, commercialization of higher technical success rate was higher compatibility. On the other hand, were observed and expected success rate were higher when a rather commercialized technologies independently be earlier than if participating in joint research in the development of the technology, unlike previously, completeness of the prior art did not significantly affect. This study has the following policy implications. Public research institutions have developed technologies are commercialized to figure out what the requirements of the technical aspects of consumer technologies in order to create economic wealth. And for technology commercialization for enough technical competencies to absorb the technology, and that the technology and considering the link between business and technology commercialization success to be applied. This study has some limitations. First, the sample size was not sufficient. In relation to the presence and participation of corporate success and commercialization of the R & D process, with many previous studies are needed more in-depth analysis by leading research in the sense that different results are obtained. Also did not reflect the will or the corporate culture, management and organizational skills and belongs to the external environment and internal corporate enterprises industry characteristics affecting the success of corporate management of the business. And lacked sufficient consideration of the various technical characteristics present in the form of joint research and industry. Finally, there is a limit of generalizations about other industries.

• International Commerce and Information Review
• /
• v.13 no.2
• /
• pp.121-148
• /
• 2011

Korean small and medium sized firms are dramatically expanding during the past two decades. Since small and medium sized firms begun to invest overseas to cope with the external and internal business environment. the influencing factors should defined for the successful foreign investment. This paper presents the research model explaining successful knowledge transfer between Korean small and medium sized firms and partners for foreign investment. This model examines investing companies' organizational characteristics, partners' learning capability and relational characteristics between two partners. Detail variables include the learning culture and codifiability of investing companies, and absorptive capability of partners, and communication and trust as a relational factors between investing companies and partners. The result of empirical analysis of sample companies shows that knowledge culture and codifiability of investing companies, and communication from the relational factors are important for knowledge transfer. These results provide some implications for the successful foreign investment of small and medium sized firms. Firstly the investing company should develop its own learning culture and internal procedure for the successful foreign investment. And frequent communication channel is necessary for knowledge transfer and the trustful relationship between investors and partner.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.6 no.3
• /
• pp.177-191
• /
• 2011

A community of practice (CoP) is a group of people who share an interest, a craft, and/or a profession. The group can evolve naturally because of the members' common interest in a particular domain or area, or it can be created specifically with the goal of gaining knowledge related to their field. It is through the process of sharing information and experiences with the group that the members learn from each other, and have an opportunity to develop themselves personally and professionally. This study focus on the 151 researchers of four government research institutes(GRIs) and research empirically an operational characteristics and performanceof CoP. Results show that characteristics like a new member increase, external linkage oriented- challenging climate, diversity oriented- autonomous climate affect a CoP performance. But external factors such as the number of participants, meeting frequency are not related with the CoP performance.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.6
• /
• pp.231-237
• /
• 2020

The purpose of this study is to present theoretical and policy implications based on the results of the empirical analysis of job stress in consideration of insufficient prior research on the level of job stress by public officials in charge of social welfare and public officials in general administration. For this purpose, social welfare and general administrative positions working at the City Hall of G Metropolitan City and five autonomous districts(including the Dong community service center) were selected as subjects for research. The data analysis used the SPSS statistical program to obtain technical statistics based on the average of the lower variables of the job stress. According to the analysis, there is a difference in the subjective perception level of public officials in charge of social welfare and public officials in general administration in both internal factors of job, such as job demands and job autonomy and external factors of job, such as job insecurity, organizational system, conflict of relations, inadequate compensation, and job culture. Based on this, it presented policy measures that require the granting of self-esteem of public officials in charge of social welfare, improvement of their duties, and adjustment of their workload to an appropriate level.

• Asia pacific journal of information systems
• /
• v.24 no.4
• /
• pp.443-472
• /
• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.15 no.4
• /
• pp.193-216
• /
• 2020

Due to the recent mid- to long-term slump and falling growth rates in the global economy, interest in organizational structures that create new products or services as a new alternative to survive and develop in an opaque environment both internally and externally, and enhance organizational sustainability through changes in production methods and business innovation is increasing day by day. In this atmosphere, we agree that the growth of small and medium-sized venture companies has a significant impact on the national economy, and various efforts are being made to enhance the technological innovation capabilities of the members so that these small and medium-sized venture companies can enhance and sustain their performance. The purpose of this study is also to investigate how the technological innovation capabilities of small and medium-sized venture companies correlate with the performance of knowledge management and to analyze the role of network capabilities to organize the strategic activities of enterprise to obtain the resources and organizational capabilities to be used for value creation from external networks. In other words, research was conducted on the impact of technological innovation capabilities of small and medium venture companies on knowledge management performance by using network capabilities as parameters. Therefore, in this study, we would like to verify the hypothesis that innovation capabilities will have a positive impact on knowledge management performance by using network capabilities of small and medium venture companies. Economic activities based on technological innovation capabilities should respond quickly to new changes in an environment where uncertainty has increased, and lead to macro-economic growth and development as well as overcoming long-term economic downturns so that they can become the nation's new growth engine as well as sustainable growth and survival of the organization. In addition, this study was conducted by setting the most important knowledge management performance within the organization as a dependent variable. As a result, R&D and learning capabilities among technological innovation capabilities have no impact on financial performance. In contrast, it was shown that corporate innovation activities have a positive impact on both financial and non-financial performance. The fact that non-financial factors such as quality and productivity improvement are identified in the management of small and medium-sized venture companies utilizing their technological innovation capabilities is contrary to a number of studies by those corporate innovation activities affect financial performance during prior research. The reason for this result is that research companies have been out of start-up companies for more than seven years, but sales are less than 10 billion won, and unlike start-up companies, R&D and learning capabilities have more positive effects on intangible non-financial performance than financial performance. Corporate innovation activities have been shown to have a positive (+) impact on both financial and non-financial performance, while R&D and learning capabilities have a positive (+) impact on financial performance by parameters of network capability. Corporate innovation activities have been shown to have no impact on both financial and non-financial performance, and R&D and learning capabilities have no impact on non-financial performance. It could be seen that the parameter effects of network competency are limited to when R&D and learning competencies are derived from quantitative financial performance. It could be seen that the parameter effects of network competency are limited to when R&D and learning competencies are derived from quantitative financial performance.

• Journal of Intelligence and Information Systems
• /
• v.26 no.4
• /
• pp.27-65
• /
• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of Global Scholars of Marketing Science
• /
• v.8
• /
• pp.233-267
• /
• 2001

The management environment in Korea today is undergoing rapid changes; in particular, domestic corporations and businesses are confronting formidable adversity with IMF crisis and WTO. Though cost cutback, higher quality, rapid production, and diversification of products were accepted as important requirements for competitiveness in the past, they have been replaced by brand power. Consumption patterns have changed their focus from function to image orientation. This is why managers in corporations have invested enormous amounts of resources into producing powerful brands, which can attract consumers' attention greatly enough to improve the image of their products. Brands are regarded as a vital vehicle for marketing strategies and thus as a legal asset. Brands with remarkable and favorable image can secure a loyal consumer groups stable revenues. M & A, currently active between corporations, makes brand equity all the more important. The purpose of the present study was to investigate the effect of internal marketing and increased brand diversification on brand equity by combining them as influential factors with marketing mix factor. For this purpose, literature review was make on previous fragmented studies of influential factors on brand equity build-up. Based on the findings of this study, some operational implications were suggested for marketing managers. The findings and implications of the present study are as follows; First, efficient communication among organization members was found to have a significant effect on product quality. Second, job satisfaction and efficient communication among members was shown to significantly influence price policies. Thirdly, efficient communication among organization workers proved to have a significant effect on distribution strategies. Forth, efficient communication among members was demonstrated to significantly influence advertisement and other public-relations activities. Fifth, opacity of market environment appeared to have a significant effect on product quality, prior market entrance as perceived by organization members turned to be of negative influence on product quality. Sixth, opacity of market environment was found to have a significant effect on price policies. Seventh, opacity of market environment was shown to be of significant effect on distribution strategies. Eighth, grater opacity of market environment proved to improve advertisement and other public-relations activities. Ninth, price policies, distribution strategies, advertisement and public-relations activities were found to have a significant effect on brand equity value. To sum up these findings, in order for corporations and businesses to cope with consumers' needs that are increasingly segmented, internal marketing strategies and brand diversification should be implemented so as to generate greater synergy effect. It is also important to stress that differentiated, higher competitiveness should be secured for Korean corporations and businesses to survive in the drastically changing, globalized market environment. In this regard, continuous and long-term management strategies for brand equity build-up should be ensured and is essential in the present unlimited competition. The last but not least important point to notice is that to increase brand equity value, intensive investment and constant emphasis should be made on internal marketing management on intra-organizational members before strengthening external marketing.