This study aims to develop a comprehensive predictive model for Digital Quality Management (DQM) and to analyze the impact of various quality activities on different levels of DQM. By employing the Classification And Regression Tree (CART) methodology, we are able to present predictive scenarios that elucidate how varying quantitative levels of quality activities influence the five major categories of DQM. The findings reveal that the operation level of quality circles and the promotion level of suggestion systems are pivotal in enhancing DQM levels. Furthermore, the study emphasizes that an effective reward system is crucial to maximizing the effectiveness of these quality activities. Through a quantitative approach, this study demonstrates that for ventures and small-medium enterprises, expanding suggestion systems and implementing robust reward mechanisms can significantly improve DQM levels, particularly when the operation of quality circles is challenging. The research provides valuable insights, indicating that even in the absence of fully operational quality circles, other mechanisms can still drive substantial improvements in DQM. These results are particularly relevant in the context of digital transformation, offering practical guidelines for enterprises to establish and refine their quality management strategies. By focusing on suggestion systems and rewards, businesses can effectively navigate the complexities of digital transformation and achieve higher levels of quality management.
This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies – Bitcoin, Ethereum, Litecoin, and EOS – and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies – AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet – representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning- based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.
본 연구는 제5차 국가산림자원조사(2006-2010)에서 조사된 편백을 대상으로 흉고직경에 따른 수고 생장곡선식과 초기 수고생장 모델을 개발하여 편백의 초기 생장특성을 고려한 합리적인 산림경영계획 수립에 필요한 기초자료를 제공할 목적으로 실시하였다. 연구자료는 제5차 국가산림자원조사 자료 중 편백 표준목 353본에 대한 수고, 흉고직경, 연륜생장 자료를 이용하였다. 흉고직경에 따른 수고 생장곡선식은 Petterson 식, Log 식, Michailow 식을 이용하여 개발하였으며, 연령에 따른 초기 수고생장 모델은 Chapman-Richards 식, Gompertz 식, Schumacher 식을 이용하여 개발하였다. 본 연구 결과, 모델 검정을 통하여 흉고직경에 따른 수고 생장곡선식은 Petterson 식이 가장 적합한 것으로 나타났으며, 초기 수고생장 모델은 Gompertz 식이 가장 적합한 것으로 나타났다. 본 연구에서 개발한 초기 수고생장 모델을 그래프로 나타낸 결과 편백은 13년생일 때 연간 수고생장량이 0.54m로 가장 많은 것으로 나타났다. 본 연구 결과는 편백의 생장 특성 관련 연구에 활용할 수 있을 뿐 아니라 초기의 편백 조림지에 대하여 합리적인 산림경영계획 수립에 유용한 기초자료가 될 것으로 기대된다.
Solenopsis geminata has been found in South Korea, suggesting a risk of its invasion has been increased by rapid climate change. This situation requires species distribution modeling to predict possibility of Solenopsis geminata introduction, but information necessary for performing it is very limited. In this study, we developed a map for global distribution of Solenopsis geminata so that the map can be used for future species distribution modeling. Also, as the first step to assess Solenopsis geminata introduction, climatic similarity between its origin (Puerto Rico) and major cities in South Korea was compared. We used ArcMap (version 10.0) for creating the distribution map by obtaining current habitat from public database, and CLIMEX was used to compare climates based on CMI value. The result showed that climates were not similar as indicated by CMI less than 0.52, suggesting the risk of intial introduction is low under the current climatic condition. However, it should be noted that climatic similarity did not consider biological characteristics of Solenopsis geminata and climate change. Thus, the next study will be devoted to climatic suitability simultaneously considers meteorological data, distribution and biological information.
The flow of the 4th Industrial Revolution calls for the innovation of the traditional business models of the manufacturers. Servitization is a corporate strategy to respond to changes in the business environment. These days, the value that the market demands can be created on the basis of the product-service integration. Thus the manufacturers must pursue the fundamental innovation of the current strategy and business models. It is necessary to create common values with customers through providing product-service integrated offerings beyond the development, production, and delivery. The purpose of this study is to develop the evaluation indicators for selecting suppliers when the manufacturer who offers the value of product-service integration needs to obtain the resources from outside. The case company in this study is the manufacture firm conducting the retail IoT business as a new business. The Delphi method is used to develop the evaluation indicators for selecting suppliers. This study suggests the academic implications providing the perspective of Servitizaiton by using Delphi method, and the practical implications applying the creating value method of Servitization by collecting the opinions from both value providers and value consumers in the process of developing the evaluation indicators.
To investigate the value co-creation process in wellness tourism, this study constructed a structural equation model of customer interactions with (1) the environment, (2) service employees, and (3) other customers relating to customer-perceived value and customer engagement. Empirical data were collected from 528 survey respondents who were at wellness tourism resorts. The results reveal that all three types of interaction have positive effects on customer-perceived value, and that perceived value positively affects customer engagement. Based on this finding, management recommendations for wellness tourism service enterprises are given.
As a system complexity increases and technology innovation progresses rapidly, leasing the equipment is considered as an important issue in many engineering areas. In practice, many engineering fields lease the equipment because it is an economical way to lease the equipment rather than to own the equipment. In addition, as the maintenance actions for the equipment are costly and need a specialist, the lessor is responsible for the maintenance actions in most leased contract. Hence, the lessor should establish the optimal maintenance strategy to minimize the maintenance cost. This paper proposes two periodic preventive maintenance policies for the leased equipment. The preventive maintenance action of policy 1 is performed with a periodic interval, in which their intervals are the same until the end of lease period. The other policy is to determine the periodic preventive maintenance interval minimizing total maintenance cost during the lease period. In addition, this paper presents two decision-making models to determine the preventive maintenance strategy for leased equipment based on the lessor’s preference between the maintenance cost and the reliability at the end of lease period. The structural properties of the proposed decision-making model are investigated and algorithms to search the optimal maintenance policy that are satisfied by the lessor are provided. A numerical example is provided to illustrate the proposed model. The results show that a maintenance policy minimizing the maintenance cost is selected as a reasonable decision as the lease term becomes shorter. Moreover, the frequent preventive maintenance actions are performed when the minimal repair cost is higher than the preventive maintenance cost, resulting in higher maintenance cost.
As the global uncertainty of manufacturing has increased and the quality problem has become global, the recall has become a fatal risk that determines the durability of the company. In addition, as the convergence of PSS (product-service system) product becomes common due to the development of IT convergence technology, if the function of any part of hardware or software does not operate normally, there will be a problem in the entire function of PSS product. In order to manage the quality of such PSS products in a stable manner, a new approaches is needed to analyze and manage the hardware and software parts at the same time. However, the Fishbone diagram, FTA, and FMEA, which are widely used to interpret the current quality problem, are not suitable for analyzing the quality problem by considering the hardware and software at the same time. In this paper, a quality risk assessment model combining FTA and FMEA based on defect rate to be assessed daily on site to manage quality and fishbone diagram used in group activity to solve defective problem. The proposed FTA-FMEA based risk assessment model considers the system structure characteristics of the defect factors in terms of the relationship between hardware and software, and further recognizes and manages them as risk. In order to evaluate the proposed model, we applied the functions of ITS (intelligent transportation system). It is expected that the proposed model will be more effective in assessing quality risks of PSS products because it evaluates the structural characteristics of products and causes of defects considering hardware and software together.
For the asset management of a water pipe network, it would be necessary to understand the extent of the maintenance cost required for the water pipe network for the future. This study would develop a method to draw the optimum cost required for the maintenance of the water pipe network in waterworks facilities to maintain the aim revenue water ratio and to achieve the target revenue water ratio, considering the water service providers’ waterworks condition and revenue water ratio comprehensively. This study conducted a survey with 96 water service providers as of the early 2015 and developed models to estimate the optimum maintenance cost of the water pipe network, considering the characteristics of the water service providers. Since the correlation coefficient of all the developed models was higher than 0.95, it turned out that it had significant reliability, which was statistically significant. As a result of applying the developed models to the actual water service providers, it was drawn that increasing revenue water ratio to more than a certain level can reduce the maintenance cost of the water pipe network by a great deal. In other words, it is judged that it would be the most efficient to secure the reliability of waterworks management by increasing the short-term revenue water ratio to more than a certain level and gradually increase the revenue water ratio from the long-term perspective. It is expected that the proposed methodology proposed in this study and the results of the study will be used as a basic research for planning the maintenance of water pipe network or establishing a plan for waterworks facilities asset management.
The purpose of the study was to investigate the causal relationships among factors affecting L2 reading achievement using a structural equation modeling (SEM) analysis. A total of 327 Korean EFL high school students completed a questionnaire on L2 reading motivation and strategies. The students’ L2 listening and reading comprehension abilities were measured by scores on the practice test for Scholastic Aptitude Test (PSAT) and self-assessed listening and reading proficiency. The study results showed that the students’ L2 reading efficacy, L2 reading strategy use, and L2 listening skills were significant predictors of their L2 reading achievement, while L2 reading motivation showed no significant relation with reading achievement. The nonsignificant path loading between reading motivation and reading achievement implies that reading motivation alone is not sufficient to promote students’ L2 reading proficiency. The final SEM model indicated a relatively strongest contribution of L2 listening ability over L2 reading efficacy and strategy use to L2 reading achievement. Pedagogical implications based on the findings are discussed.
In this research, technology innovation capability evaluation model for small and medium enterprises was developed. To develop technology innovation capability evaluation model, two analytic technic was used. First one is AHP (Analytic Hierarchy Process) to give weight to each main index. Second one is fuzzy set theory to represent ambiguous index to numerical value. Finally, technology innovation capability evaluation model was achieved in combination with the same weight to AHP analysis and fuzzy set theory. With these results, small and medium enterprises can know important point in terms of strengthening the innovation capability evaluation.
This study aims to develop an English writing model using pattern-based reading materials and to apply it to the elementary classroom. The meaning of “patterns” was searched for in the language learning and teaching methods, and their roles were examined in terms of language acquisition and learning. The writing class was connected to the reading class so that learners could properly model and transfer their forms and meanings of the patterns recognized in the reading class to what they want to write in the writing class. The experiment was conducted on one class of grade 6 elementary school students in which the reading and writing class was integrated into the regular English class during one semester. Six pattern-based reading materials were selected with a range of genres including stories and poems. The effect of the pattern-based reading materials on the writing class was examined through writing test and a questionnaire about the affective domain before and after the experiment. The result showed that writing scores were increased significantly in all the leveled-group learners. As for the affective domain, interest, participation, confidence, and adventure each had a significantly increased score. The sense of adventure increased the most. This is considered attributable to the feedback which ignored grammatically trivial errors and focused on how to properly express the contents learners wanted to write.