• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.1-36
• /
• 2020

This study is to reveal the acceptance factors of the Market Sentiment Index (MSI) created by reflecting the investor sentiment extracted by processing unstructured big data. The research model was established by exploring exogenous variables based on the rational behavior theory and applying the Technology Acceptance Model (TAM). The acceptance of MSI provided to investors in the stock market was found to be influenced by the exogenous variables presented in this study. The results of causal analysis are as follows. First, self-efficacy, investment opportunities, Innovativeness, and perceived cost significantly affect perceived ease of use. Second, Diversity of services and perceived benefits have a statistically significant impact on perceived usefulness. Third, Perceived ease of use and perceived usefulness have a statistically significant effect on attitude to use. Fourth, Attitude to use statistically significantly influences the intention to use, and the investment opportunities as an independent variable affects the intention to use. Fifth, the intention to use statistically significantly affects the final dependent variable, the intention to use continuously. The mediating effect between the independent and dependent variables of the research model is as follows. First, The indirect effect on the causal route from diversity of services to continuous use intention was 0.1491, which was statistically significant at the significance level of 1%. Second, The indirect effect on the causal route from perceived benefit to continuous use intention was 0.1281, which was statistically significant at the significance level of 1%. The results of the multi-group analysis are as follows. First, for groups with and without stock investment experience, multi-group analysis was not possible because the measurement uniformity between the two groups was not secured. Second, the analysis result of the difference in the effect of independent variables of male and female groups on the intention to use continuously, where measurement uniformity was secured between the two groups, In the causal route from usage attitude to usage intention, women are higher than men. And in the causal route from use intention to continuous use intention, males were very high and showed statistically significant difference at significance level 5%.

• Journal of Distribution Science
• /
• v.8 no.1
• /
• pp.21-33
• /
• 2010

The ICT(information & communication technology) led to a dramatic change of floral distribution service, a phase of competition between wholesales and retail stores, and distribution channels in floral industry. It was expected that a role of the intermediaries in this industry would have reduced due to the improvement of transaction process by ICT. However, the ICT made to overcome a regional limit of the floral retail distribution service leading to an increase in sales and enlargement of the stores. And even it made possible to bring out another type of intermediaries such as private associations. This case study focuses on what kinds of efforts the floral wholesale distributors have made to enable a distribution process more smoothly between the wholesale distributors and retail stores through the information system, and what the failure factors in adopting the information system have been. This paper is also to examine how the wholesale distributors have changed themselves to gain dominant positions in distribution channels. As a result of the study, it was found that the intermediaries mostly failed in successfully achieving the distribution channel innovation through the information system because of several main reasons. FLOMARKET Inc. tried to innovate a distribution channel to obtain high quality goods through consolidating a wholesale distribution market in that segregated both floral joint market from free markets. after implementing the information system with consideration of the failure factors, FLOMARKET Inc. was able to minimize goods in stock and make a major purchase of various goods. In addition, it made a possible pre-ordering process and an exact calculation of purchasing goods so they could provide their products with market price in real time, which helped for the company to gain credits from their customers. Also, FLOMARKET Inc. established the information system which well suited to its business stage in order to deal with a rapidly changing distribution environment. It's so obvious that the transaction processing system of FLOMARKET Inc. definitely helped to share information among traders more seamlessly and smoothly in realtime, standardize goods, and make a transaction process clearer. Besides, the transaction information helped the wholesale distributors and retail stores to make more strategic decisions in their business because through the system they enabled to gather the marketing intelligence information more easily and convenient. If we understand that the floral distribution market is characterized by the low IT- based industry, it's worth to examine a case study proving that the information system actually increases the productivity of the transaction process in the floral industry.

• Journal of Technology Innovation
• /
• v.26 no.4
• /
• pp.199-232
• /
• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• Knowledge Management Research
• /
• v.22 no.2
• /
• pp.119-144
• /
• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Information Systems Review
• /
• v.19 no.2
• /
• pp.1-19
• /
• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.107-129
• /
• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.93-111
• /
• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Global Scholars of Marketing Science
• /
• v.19 no.1
• /
• pp.9-21
• /
• 2009

Recently, the researches to explain Switching Behavior through Theory of Planned Behavior have been discovered. Many researches say that System factors of mobile telecommunication service(MTS) is positively associated with Switching Intention. But There is no difference of system factors between mobile telecommunication services because of IT technique Development. Thus, this study investigated whether switching cost and alternative's attractiveness influence switching intention concerning mobile telecommunication service by adopting Theory of Planned Behavior (TPB) as an underlying theoretical premise. The study also attempted to determine the moderating effects of personal innovativeness on switching intention. For these purposes the author has developed several hypotheses as follows: H-1. The switching cost of different MTS is associated with the attitude of MTS which is using. H-2. The switching cost of different MTS is associated with the subjective norm of MTS which is using. H-3. The switching cost of different MTS is associated with the perceived behavior control of MTS which is using. H-4. The alternative's attractiveness of different MTS is associated with the attitude of MTS which is using. H-5. The alternative's attractiveness of different MTS is associated with the subjective norm of MTS which is using. H-6. The alternative's attractiveness of different MTS is associated with the perceived behavior control of MTS which is using. H-7. The switching cost of different MTS is associated with the switching intention. H-8. The alternative's attractiveness of different MTS is associated with the switching intention. H-9. The attitude of MTS is associated with the switching intention. H-10. The subjective norm of MTS is associated with the switching intention. H-11. The perceived behavior control of MTS is associated with the switching intention. H-12. The personal innovativeness has been a moderating effects to switching intention. Data has been collected from 403 respondents for this study using a questionnaire method. The survey for the actual analysis of the research was done and analyzed with the customers who have an experience of using Mobile telecommunication service and the samples were selected among the middle and high school students who live in Seoul area, the university students who live in Seoul, Gyeonggi and Chungcheng Provinces, and the ordinary workers who are working in Seoul and Gyeonggi Province. The survey was done for 23 days from March 28, 2008 through April 12, 2008. The positive analysis was done with SPSS 12.0K statistics package and visual PLS program using the analysis techniques of frequency analysis, reliability analysis, correlation analysis and factor analysis. In addition, structural equation modeling was conducted using AMOS 5.0. The data was analyzed by frequency analysis using SPSS 12.0 and structural equation modeling using AMOS 5.0. The result of the overall model analysis is as follows: Chi-Square=378.306, d.f.=107, p-value=0.0, GFI=.904, AGFI= 0.863, IFI= 0.939, NFI= 0.917, RMSEA= 0.079, TLI= 0.922. The results of the overall model analysis were coherent. The following study results were revealed: First, switching cost was related positively to attitude, subjective norm and perceived behavior control, three components of TPB. Second, alternative's attractiveness was related negatively to subjective norm but positively to perceived behavior control. Third, switching cost and attitude was related negatively to switching intention, while perceived behavior control was related positively to switching intention. Finally, the study found the moderating effects of personal innovativeness on switching intention. Based on the results, the study offers marketing strategic implications for mobile telecommunication service industry.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.151-171
• /
• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.2 no.3
• /
• pp.33-60
• /
• 2007

This study alms to analyze the entrepreneur characteristics of founder on enterprise performance from the strategic viewpoint as well as features of founder of small firms such as background feature of founder, psychological features and management skill. As considered by Background features of founder include educational background of founder, his experience in business creation, consultation or course related to business creation. This study verified the effects of factor which business performance (financial, non financial) on small firms. Also, this study considered psychological features of founder include achievement desire, risk-free propensity, level of patience on vagueness and control position. And it analyzed that between such factors and performance of small firms were examined in related. In the mean time, management ability of founder, entrepreneur ability, technical and function ability were considered for management skill of founder and alalyzed effect of the factors on performance of small firm were examined. Effects of strategic intention of founder of small firm were analyzed by the strategic viewpoint. At this time, strategy of small firm was divided into product-service reform differentiation strategy, marketing differentiation strategy and cost leadership strategy. This study distributed questionnaire on CEO of small firms in Daejeon and Chungnam area for accomplish the study objective and it collected a total of 145 copies of questionnaires. As a result of analyzing collected questionnaire, this study deduced the following study results and suggestions. First, results different from those of existing studies were found Since sales, net income and profit rate of small firm were not high cause economic depression on the whole. Second, entrepreneur ability was found to be required for success of business creation. Entrepreneur ability of founder was the factor that affects both financial and non - financial performance of small firm. As such, entrepreneur ability can be regarded as the most important factor for success in business creation of small firm. Accordingly, entrepreneur ability is the most important source for success in business creation of small firm. Third, strategy of small firm was found to be the important factor that affects the non-financial performance even if it could not give significant effects on financial performance. Thus, product service reform differentiation strategy, marketing differentiation strategy and cost leadership strategy have significant effects on non - financial performance of small firm. Accordingly, it is required to operate small firm with strategic mind - set for small firm to achieve success. This study analyzed the effects of feature of founder and strategy of small firm on business performance of small firm through practical analysis on small firms in Daejeon and Chungnam area, and deduced meaningful results. However, Since this study collected data on small firms in Daejeon and Chungnam only, there is a limit in generalizing the results of this study to all small firms in Korea. Companies answering to this questionnaire process were mainly wholesale and retail service companies. In addition, there is a limit in that it failed to analyze feature of representative type of industry due to limit in number of sample, it is required to divide representative type of industry and to compare and analyze types of industry in future studies.