• The Journal of Bigdata
• /
• v.3 no.1
• /
• pp.83-94
• /
• 2018

The purpose of this study is to investigate how startup companies with the UGC platform service model can traverse the death valley for the company's survival with limited resources and create a mutually beneficial market. To do this, an interview-based exploratory study was conducted to analyze the cause and effect of each factor on the initial activation strategy of the UGC platform. For many start-up companies, this research helps minimize errors in strategic trial and error.

• Asia pacific journal of information systems
• /
• v.12 no.4
• /
• pp.21-36
• /
• 2002

This study empirically examined the effects of data warehousing methodology on the success of data warehousing. Research model and two hypotheses were set up to identify the relationships among two types of data warehousing methodology(top-down/bottom-up, dw configuration) and success based on the investigations of such theories as data warehousing, data warehousing methodology, IS success and so forth. And the survey instrument(questionnaire) was developed to collect data. Ultimately 183 questionnaires from 61 korean firms were collected. Findings showed that two types of data warehousing methodology affect significant effect on the success of data warehousing.

• The Korean Journal of Applied Statistics
• /
• v.12 no.1
• /
• pp.81-81
• /
• 1999

A categorical data analysis system in the World Wide Web is proposed with an easy- to-use environment . This system is composed of four components. First, this system presents several graphical displays for Exploratory Data Analysis for categorical data. Second, it provides some measures of association Including dynamic graphics for mosaic plots of Hartigan and Kleiner (1981) and Friendly (1994). Dynamic graphics for mosaic plots give some useful informations. Third, this system can analyze categorical data with loglinear models. So we can select the best fitted loglinear model interactively.

• Journal of Distribution Science
• /
• v.15 no.4
• /
• pp.69-78
• /
• 2017

Purpose - The study was AI as exploratory study on artificial intelligence (AI) shopping information services, to explore the possibility of a new business of the distribution industry. For research, we compare to IBM of consumer awareness surveys an AI shopping information service for retailing channel and target goods group. Finally, we present to service scenario for distribution service using AI. Research design, data, and methodology - First, to identify possible the success of the information service shopping using AI, AI technology for the consumer is very important for the acceptance of judgement. Therefore, we explored the possibility of AI information service for business as a shopping. The experimental data were used to interpret the meaning of the relevant literature and the IBM Institute of Business Value (IBV) Report 2015. This research is based on the use of a technical acceptance model (TAM) to determine whether the consumer would adopt the 'AI shopping information service' technology. Step 1 of the process assumes that the consumer adopts AI technology. In step 2, consumers find their preference channels and goods targeted at them as per their preferences. Finally Step 3, we present scenario for 'AI shopping information service' based on the results of Step 1 and 2. Results - Consumers have expressed their high interests in the new shopping information services, especially the on/off line distribution channels can use shopping information to increase the efficiency in provision of goods. Digital channel (such as SNS, online shopping etc.) is especially high value goods such as cars, furniture, and home appliances by displaying it to an appropriate product group. Conclusions - The study reveals the potential for the use of new business models such as 'AI shopping information service' by the distribution industry. We present seven scenario related AI application refer from IBM suggestion, and the findings would enable the distribution industry to approach target consumers with their products, especially high value goods. 'Shopping advisor' is considered to the most effective. In order to apply to the other field of the distribution industry business, which utilizes AI technology, it should be accompanied by additional empirical data analysis should be undertaken.

• Asia pacific journal of information systems
• /
• v.7 no.2
• /
• pp.225-266
• /
• 1997

A Causal Transition Model of the IT impact on organization is proposed. The model is based upon the premise that the IT impact is a multi-phase, multi-realm phenomenon, and that the IT impact in one organizational realm logically transpires to another realm, thus forming complex causal webs among them. Two exploratory research studies, the one qualitative and the other quantitative, were conductea to validate the model in a setting involving major structural reorganization of the organizations' IT function. The research results provide support for the general theory structure of the model. The findings include: ⅰ) the IT impact manifests on multiple organizational realms, with different degrees of strength, ⅱ) the impact on the realms follow a particular causal transition path among them, and ⅲ) the IT impact manifests on and through the information processing aspect of work. The results, however, indicate that people's perception of the IT impact is strongly mitigated by the IT relevance of work, and that the organization is affected as much by the structural arrangement surrounding and accompanying the IT as by the technology itself, suggesting that the IT impact is an organizational phenomenon as well as a technological phenomenon. The implications of the research results are discussed at the end.

• Journal of information and communication convergence engineering
• /
• v.15 no.3
• /
• pp.165-169
• /
• 2017

Altmetrics is an emergent research area whereby social media is applied as a source of metrics to evaluate scientific impact. Recently, the interest in altmetrics has been growing. Traditional scientific impact evaluation indictors are based on the number of publications, citation counts and peer reviews of a researcher. As research publications were increasingly placed online, usage metrics as well as webometrics appeared. This paper explores the potential benefits of altmetrics and the deep relationship between each metrics. Firstly, we found a weak-to-medium correlation among the 11 altmetrics and visualized such correlation. Secondly, we conducted principal component analysis and exploratory factor analysis on altmetrics of social media, divided the 11 altmetrics into four feature sets, confirming the dispersion and relative concentration of altmetrics groups and developed the altmetrics evaluation model. We can use this model to evaluate the scientific impact of articles on social media.

• Asia pacific journal of information systems
• /
• v.3 no.1
• /
• pp.54-87
• /
• 1993

This exploratory study addressed the issue of effective EUC management, based on the sociotechnical theory. Extensive literature review gave birth to a set of critical success factors in EUC. With those factors, a basic EUC model was developed. Then the model was tested in the domestic industry to find its validity. It was also attemped to develop a structural equation model in which critical factors for sucessful implementation of EUC are arranged by the result of empirical survey. In the final model, technical support, computer experience, user control, and top management support were included as exogenous factors. Thses contructs were found to influence directly or indirectly three endogenous factors, user satisfaction, computer use, and performance.

• Journal of Family Resource Management and Policy Review
• /
• v.11 no.4
• /
• pp.55-71
• /
• 2007

The purpose of this study was to explore a self-diagnostic indicator for measuring a healthy family by adopting the theme of "happiness", which has surfaced as the most interesting in many academic fields recently. Though the basic concept of a healthy family may be shared by everyone, the criterion of happiness varies from one family to another. Therefore, it is desirable that the tool be made in such a way that every member of the family can check their health from a holistic perspective, rather than diagnosing health and happiness from the perspective of professionals. So, this study was aimed at diagnosing a family by using a tool named GAMMA model, so each family member can recognize problems and find the best options to solve it. This study. has a significant meaning in that it has tried to diagnose families by introducing the GAMMA model into domestic science for the first time.

• Nutrition Research and Practice
• /
• v.10 no.4
• /
• pp.464-470
• /
• 2016

BACKGROUND/OBJECTIVES: This research analyzes the effects of the food choices of industrial workers according to their sugar intake pattern on their job satisfaction through the construction of a model on the relationship between sugar intake pattern and job satisfaction. SUBJECTS/METHODS: Surveys were collected from May to July 2015. A statistical analysis of the 775 surveys from Kyungsangnam-do was conducted using SPSS13.0 for Windows and SEM was performed using the AMOS 5.0 statistics package. RESULTS: The reliability of the data was confirmed by an exploratory factor analysis through a Cronbach's alpha coefficient, and the measurement model was proven to be appropriate by a confirmatory factor analysis in conjunction with AMOS. The results of factor analysis on food choice, sugar intake pattern and job satisfaction were categorized into five categories. The reliability of these findings was supported by a Cronbach's alpha coefficient of 0.6 and higher for all factors except confection (0.516) and dairy products (0.570). The multicollinearity results did not indicate a problem between the variables since the highest correlation coefficient was 0.494 (P < 0.01). In an attempt to study the sugar intake pattern in accordance with the food choices and job satisfaction of industrial workers, a structural equation model was constructed and analyzed. CONCLUSIONS: All tests confirmed that the model satisfied the recommended levels for the goodness of fit index, and thus, the overall research model was proven to be appropriate.

• Nutrition Research and Practice
• /
• v.8 no.4
• /
• pp.432-438
• /
• 2014

BACKGROUND/OBJECTIVES: This research was conducted to develop a construct model regarding the dietary style, late night snacking choice attributes and health promotion behaviors of industrial workers. SUBJECTS/METHODS: The surveys were collected during the period between January and February 2013. A statistical analysis of 888 industrial workers was conducted using SPSS 12.0 for Windows and SEM (Structural Equation Model) using AMOS (Analysis of Moment Structure) 5.0 statistics package. RESULTS: The results of the correlations between all variables showed significant positive correlations (P < 0.05). Results of factors analysis on dietary styles were categorized into five factors and health promotion behaviors were categorized into four. The reliability of these findings was supported by a Cronbach's alpha coefficient of 0.6 and higher for all other factors. After obtaining the factors from processing an exploratory factor analysis and the end results supported the validity. In an attempt to study the late night snacking choice attributes in accordance to dietary styles and the health promotion behaviors of industrial workers, a structural equation model was constructed and analyzed. CONCLUSIONS: All tests proved the model satisfied the recommended levels of the goodness on fit index, and thus, the overall research model was proved to be appropriate.