Purpose: Since 2005, the Ministry of Health & Welfare has provided financial support to promote palliative care for terminal cancer patients. We analyzed how palliative care facilities used the funding between 2006 and 2010. Methods: Frequency analysis was conducted by the item of expenditure based on fiscal reports of the palliative care facilities. Linear regression analysis was performed to examine a trend over time. Kruskal-Wallis test and Wilcoxon rank-sum test were used to compare expenditure items, the number of provision of financial support and type of palliative care units. Results: About a half of the fund was spent to pay care givers salary, improve facilities and purchase equipment regardless of the year, the number of financial support provided or facility type. By year, the operation cost for palliative care program and the education cost for health care workers have significantly increased in linear regression analysis (P<0.01). However, the amount of financial support for the low income group has decreased over years (P=0.024). This trend was affected by evaluation criteria and weight. Conclusion: The government aid for palliative care units has been used to improve facilities and equipment. Moreover, desirable changes were noted such as a higher portion of expenses for program operation and care giver training to enhance the quality of care. However, the evaluation criteria need to be adjusted to prevent any further decrease in the support provided to the low income group.
The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.
Even though assessment using information and communication technology will most likely lead the future of educational assessment, there is little domestic research on this topic. Computerized assessment will not only cut costs but also measure students' performance in ways not possible before. In this context, this study introduces a tool which can overcome the problems of multiple choice tests, which are most widely used type of assessment in current Korean educational setting. Multiple-choice tests, in which options are presented with the questions, are efficient in that grading can be automated; however, they allow for students who don't know the answer, to find the correct answer from the options. Park(2005) has developed a modified multiple-choice testing system (CMMT) using the interactivity of computers, that presents questions first, and options later for a short time when the student requests for them. The present study was conducted to find out if penalizing wrong answers could lower the possibility of students choosing an answer among the options when they don't know the correct answer. 116 students were tested with the directions that they will be penalized for wrong answers, but not for no response. There were 4 experimental conditions: 2 conditions of high or low percentage of penalizing, each in traditional multiple-choice or CMMT format. The results were analyzed using a two-way ANOVA for the number of no response, the test score and self-report score. Analysis showed that the number of no response was significantly higher for the CMMT format and that test scores were significantly lower when the penalizing percentage was high. The possibility of applying CMMT format tests while penalizing wrong answers in actual testing settings was addressed. In addition, the need for further research in the cognitive sciences to develop computerized assessment tools, was discussed.
Until recently, successful implementation of ERP systems has been a popular topic among ERP researchers, who have attempted to identify its various contributing factors. None of these efforts, however, explicitly recognize the need to identify disparities that can exist between organizational information requirements and ERP systems. Since ERP systems are in fact "packages" -that is, software programs developed by independent software vendors for sale to organizations that use them-they are designed to meet the general needs of numerous organizations, rather than the unique needs of a particular organization, as is the case with custom-developed software. By adopting standard packages, organizations can substantially reduce many of the potential implementation risks commonly associated with custom-developed software. However, it is also true that the nature of the package itself could be a risk factor as the features and functions of the ERP systems may not completely comply with a particular organization's informational requirements. In this study, based on the organizational memory mismatch perspective that was derived from organizational memory theory and cognitive dissonance theory, we define the nature of disparities, which we call "mismatches," and propose that the mismatch between organizational information requirements and ERP systems is one of the primary determinants in the successful implementation of ERP systems. Furthermore, we suggest that customization efforts as a coping strategy for mismatches can play a significant role in increasing the possibilities of success. In order to examine the contention we propose in this study, we employed a survey-based field study of ERP project team members, resulting in a total of 77 responses. The results of this study show that, as anticipated from the organizational memory mismatch perspective, the mismatch between organizational information requirements and ERP systems makes a significantly negative impact on the implementation success of ERP systems. This finding confirms our hypothesis that the more mismatch there is, the more difficult successful ERP implementation is, and thus requires more attention to be drawn to mismatch as a major failure source in ERP implementation. This study also found that as a coping strategy on mismatch, the effects of customization are significant. In other words, utilizing the appropriate customization method could lead to the implementation success of ERP systems. This is somewhat interesting because it runs counter to the argument of some literature and ERP vendors that minimized customization (or even the lack thereof) is required for successful ERP implementation. In many ERP projects, there is a tendency among ERP developers to adopt default ERP functions without any customization, adhering to the slogan of "the introduction of best practices." However, this study asserts that we cannot expect successful implementation if we don't attempt to customize ERP systems when mismatches exist. For a more detailed analysis, we identified three types of mismatches-Non-ERP, Non-Procedure, and Hybrid. Among these, only Non-ERP mismatches (a situation in which ERP systems cannot support the existing information needs that are currently fulfilled) were found to have a direct influence on the implementation of ERP systems. Neither Non-Procedure nor Hybrid mismatches were found to have significant impact in the ERP context. These findings provide meaningful insights since they could serve as the basis for discussing how the ERP implementation process should be defined and what activities should be included in the implementation process. They show that ERP developers may not want to include organizational (or business processes) changes in the implementation process, suggesting that doing so could lead to failed implementation. And in fact, this suggestion eventually turned out to be true when we found that the application of process customization led to higher possibilities of failure. From these discussions, we are convinced that Non-ERP is the only type of mismatch we need to focus on during the implementation process, implying that organizational changes must be made before, rather than during, the implementation process. Finally, this study found that among the various customization approaches, bolt-on development methods in particular seemed to have significantly positive effects. Interestingly again, this finding is not in the same line of thought as that of the vendors in the ERP industry. The vendors' recommendations are to apply as many best practices as possible, thereby resulting in the minimization of customization and utilization of bolt-on development methods. They particularly advise against changing the source code and rather recommend employing, when necessary, the method of programming additional software code using the computer language of the vendor. As previously stated, however, our study found active customization, especially bolt-on development methods, to have positive effects on ERP, and found source code changes in particular to have the most significant effects. Moreover, our study found programming additional software to be ineffective, suggesting there is much difference between ERP developers and vendors in viewpoints and strategies toward ERP customization. In summary, mismatches are inherent in the ERP implementation context and play an important role in determining its success. Considering the significance of mismatches, this study proposes a new model for successful ERP implementation, developed from the organizational memory mismatch perspective, and provides many insights by empirically confirming the model's usefulness.
Franchising is one of the fastest growing types of business. It is already popular and well-known in the U.S., and has been growing in many other countries including Korea. Furthermore, many Korean franchising companies have expanded their business overseas actively. According to the data by the Ministry of Industry and Resource, 82 companies out of a sample of 500 franchising companies are already operating in many foreign countries and 48% of them have started their foreign business since 2006. This clearly indicates the fast growing current trend of foreign operation by Korean franchising companies. In spite of the fast growing trend of foreign expansion in the industry, academic research on internationalization of franchising companies is extremely difficult to find. Accordingly, academic research on the issue is necessary and urgent in Korea. Among the various research questions on internationalization of franchising business, this study intends to investigate the difference in organizational factors between the franchising companies doing foreign operation and those doing business only domestically. More specifically, this research has the following purposes. First, considering the lack of theoretical basis of previous studies, resource-based theory and agency theory are employed as the theoretical bases. Second, this study explains the difference in internationalization based on organizational factors such as company size, history and growth rate. Third, the five hypotheses regarding the difference in organizational factors are presented and tested empirically, which is the first attempt in the area of this topic. Finally, the study attempts to clarify the conflicting implications among theories regarding some organizational factos such as growth rate. As the theoretical background, resource-based theory and agency theory are discussed. According to resource-based theory, a firm can grow continuously when it has competence and resource, and also the ability to develop them. The competence and resource can include capital, human resource, management skill, market information, ability to manage risk, etc. Meanwhile, agency theory views the relationship between franchisor and franchisee as an agency relationship. In agency theory, bonding capability and monitoring capability are the two key factors which promote internationalization of franchising companies. Based on the two theories, a conceptual model is designed. The model consists of two groups of variables. One is organizational factors including size, history, growth rate, price bonding and geographic dispersion. The other is whether a franchising company is operating overseas or not. We developed the following five research hypotheses basically describing the relationship between organizational factors and internationalization of franchising companies. H1: The size of franchising companies operating overseas is larger than that of franchising companies operating domestically. H2: The history of franchising companies operating overseas is longer than that of franchising companies operating domestically. H3: The growth rate of franchising companies operating overseas is higher than that of franchising companies operating domestically. H4: The price bonding of franchising companies operating overseas is higher than that of franchising companies operating domestically. H5: The geographic dispersion of franchising companies operating overseas is wider than that of franchising companies operating domestically. Data for the analyses are obtained from 2005 Korea Franchise Survey data co-generated by Ministry of Industry and Resource, GS1 Korea, and Korea Franchise Association. Out of 2,804 population companies, 2,489 companies are excluded for various reasons and 315 companies are selected as the final sample. Prior to hypotheses tests, validity and reliability of the measures of size, history, growth rate and price bonding are examined for further analyses. Geographic dispersion is not validated since it is measured using nominal data. A series of independent sample T-tests is used to find out whether there exists any significant difference between the companies internationalized and those operating only domestically for each organizational factor. Among the five factors, size and geographic dispersion show significant difference, growth rate and price bonding do not reveal any difference and, finally, history factor shows conflicting results in the difference depending on how to measure it.