Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.
Animal welfare is of considerable importance to European consumers and citizens, this being most recently confirmed in EU barometer studies. Researchers and others have long proposed that animal-based measures (measures taken on animals, e.g. their health and behaviour) can provide a valid indicator of animal welfare; since welfare is a characteristic of the individual animal. Therefore, a welfare assessment can be essentially based on animal-based measures, but with use of resource measures to provide the capacity to assess 'risk factors'. The first goal of this project was to develop a welfare monitoring system that enables assessment of welfare status through standardised conversion of welfare measures into accessible and understandable information. The acquired information on one hand provides feedback to animal unit managers about the welfare status of their animals, and on the other, information on the welfare status of animal-related products for consumers and retailers. The second goal of Welfare $Quality^{(R)}$ was to improve animal welfare by minimising the occurrence of harmful behavioural and physiological states, improving human-animal relationships, and providing animals with safe and stimulating environments. The different measurable aspects of welfare to be covered are turned into welfare criteria. The criteria reflect what is meaningful to animals as understood by animal welfare science. Once all the measures have been performed on an animal unit, a bottom-up approach is followed to produce an overall assessment of animal welfare on that particular unit: first the data collected (i.e. values obtained for the different measures on the animal unit) are combined to calculate criterion-scores; then criterion-scores are combined to calculate principle-scores; and finally the animal unit is assigned to a welfare category according to the principle-scores it obtained.
Mobile Multimedia File System, MNFS, is a file system which extensively exploits NAND FLASH Memory, Since general Flash file systems does not precisely meet the criteria of mobile devices such as MP3 Player, PMP, Digital Camcorder, MNFS is designed to guarantee the optimal performance of FLASH Memory file system. Among many features MNFS provides, there are three distinguishable characteristics. MNFS guarantees, first, constant response time in sequential write requests of the file system, second, fast file system mounting time, and lastly least memory footprint. MNFS implements four schemes to provide such features, Hybrid mapping scheme to map file system metadata and user data, manipulation of user data allocation to fit allocation unit of file data into allocation unit of NAND FLASH Memory, iBAT (in core only Block Allocation Table) to minimize the metadata, and bottom-up representation of directory. Prototype implementation of MNFS was tested and measured its performance on ARM9 processor and 1Gbit NAND FLASH Memory environment. Its performance was compared with YAFFS, NAND FLASH File system, and FAT file system which use FTL. This enables to observe constant request time for sequential write request. It shows 30 times faster mounting time to YAFFS, and reduces 95% of HEAP memory consumption compared to YAFFS.
Consumers of e-learning market differ from those of other markets in that they are replaced in a specific time scale. For example, e-learning contents aimed at highschool senior students cannot be consumed by a specific consumer over the designated period of time. Hence e-learning service providers need to attract new groups of students every year. Due to lack of information on products designed for continuously emerging consumers, the consumers face difficulties in making rational decisions in a short time period. Increased uncertainty of product purchase leads customers to herding behaviors to obtain information of the product from others and imitate them. Taking into consideration of these features of e-learning market, this study will focus on the online herding behavior in purchasing e-learning contents. There is no definite concept for e-learning. However, it is being discussed in a wide range of perspectives from educational engineering to management to e-business etc. Based upon the existing studies, we identify two main view-points regarding e-learning. The first defines e-learning as a concept that includes existing terminologies, such as CBT (Computer Based Training), WBT (Web Based Training), and IBT (Internet Based Training). In this view, e-learning utilizes IT in order to support professors and a part of or entire education systems. In the second perspective, e-learning is defined as the usage of Internet technology to deliver diverse intelligence and achievement enhancing solutions. In other words, only the educations that are done through the Internet and network can be classified as e-learning. We take the second definition of e-learning for our working definition. The main goal of this study is to investigate what factors affect consumer intention to purchase e-learning contents and to identify the differential impact of the factors between consumers with purchase experience and those without the experience. To accomplish the goal of this study, it focuses on herding behavior and perceived usefulness as antecedents to behavioral intention. The proposed research model in the study extends the Technology Acceptance Model by adding herding behavior and usability to take into account the unique characteristics of e-learning content market and e-learning systems use, respectively. The current study also includes consumer experience with e-learning content purchase because the previous experience is believed to affect purchasing intention when consumers buy experience goods or services. Previous studies on e-learning did not consider the characteristics of e-learning contents market and the differential impact of consumer experience on the relationship between the antecedents and behavioral intention, which is the target of this study. This study employs a survey method to empirically test the proposed research model. A survey questionnaire was developed and distributed to 629 informants. 528 responses were collected, which consist of potential customer group (n = 133) and experienced customer group (n = 395). The data were analyzed using PLS method, a structural equation modeling method. Overall, both herding behavior and perceived usefulness influence consumer intention to purchase e-learning contents. In detail, in the case of potential customer group, herding behavior has stronger effect on purchase intention than does perceived usefulness. However, in the case of shopping-experienced customer group, perceived usefulness has stronger effect than does herding behavior. In sum, the results of the analysis show that with regard to purchasing experience, perceived usefulness and herding behavior had differential effects upon the purchase of e-learning contents. As a follow-up analysis, the interaction effects of the number of purchase transaction and herding behavior/perceived usefulness on purchase intention were investigated. The results show that there are no interaction effects. This study contributes to the literature in a couple of ways. From a theoretical perspective, this study examined and showed evidence that the characteristics of e-learning market such as continuous renewal of consumers and thus high uncertainty and individual experiences are important factors to be considered when the purchase intention of e-learning content is studied. This study can be used as a basis for future studies on e-learning success. From a practical perspective, this study provides several important implications on what types of marketing strategies e-learning companies need to build. The bottom lines of these strategies include target group attraction, word-of-mouth management, enhancement of web site usability quality, etc. The limitations of this study are also discussed for future studies.
Today, businesses have to respond with flexibility and speed to ever-changing customer demand and market opportunities. Service-oriented architecture (SOA) is the best methodology for minimizing the complexity and the cost of enterprise-level infrastructure and for maximizing the productivity and the flexibility of an enterprise. Most of the enterprise-level SOA delivery strategies deal with the top-down approach, which organization has to define the business processes, to model business services, and to find the required services or to develop new services. However, a lot of peoples want to maximally reuse legacy component-based systems as well as to deliver SOA into their organizations. In this paper, we propose a bottom-up approach for identifying business services with proper granularity. It can improve the reusability and maintenance of services by considering not data I/O of components of legacy applications but GUI event patterns. Our proposed method is applied to MIS with 129 GUIs and 13 components. As a result, the valiance of the coupling value of components is increased five times and three business services are distinctly exposed. It also provides a 49% improvement in reducing the relationship problems between services over a service identification method using only partitioning information of components.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.19
no.2
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pp.197-214
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2024
This study aimed to investigate students' perceptions at science and technology specialized universities towards entrepreneurship support policies and to derive policy improvement measures by applying a bottom-up approach to reflect the requirements of the policy beneficiaries, i.e., the students. Specifically, the research explored effective execution strategies for student entrepreneurship support policies through a survey and analysis of KAIST students. The findings revealed that KAIST students recognize the urgent need for improvement in sharing policy objectives with the student entrepreneurship field, reflecting the opinions of the campus entrepreneurship scene in policy formulation, and constructing an entrepreneurship-friendly academic system for nurturing student entrepreneurs. Additionally, there was a highlighted need for enhancement in the capacity of implementing agencies, as well as in marketing and market development capabilities, and organizational management and practical skills as entrepreneurs within the educational curriculum. Consequently, this study proposes the following improvement measures: First, it calls for enhanced transparency and accessibility of entrepreneurship support policies, ensuring students clearly understand policy objectives and can easily access information. Second, it advocates for student-centered policy development, where students' opinions are actively incorporated to devise customized policies that consider their needs and the actual entrepreneurship environment. Third, there is a demand for improving entrepreneurship-friendly academic systems, encouraging more active participation in entrepreneurship activities by adopting or refining academic policies that recognize entrepreneurship activities as credits or expand entrepreneurship-related courses. Based on these results, it is expected that this research will provide valuable foundational data to actively support student entrepreneurship in science and technology specialized universities, foster an entrepreneurial spirit, and contribute to the creation of an innovation-driven entrepreneurship ecosystem that contributes to technological innovation and social value creation.
Purpose: Existing precedent studies include success factors of individual management innovation activities constantly. However, those studies have limitations about the common key success factors of individual management innovation activities. Methods: For this study, we investigate the key success factors using literature research of the most typical management innovation activities adopted and implemented by many companies in Korea, such as 6sigma, TQM, Lean 6sigma, ERP, TPM, BPR, Project Management, System Engineering. Factors emerging repeatedly was combined into common factors and inherent factors that are necessary for the success of individual management innovation activities are designated to essential factors. Results: 'Essential factors for Six Sigma' consist of 5 items. Black belt operating system, personnel management system linkage, the correct management of the data, perform improvement projects associated with financial performance financial result, linked to financial performance improvement project, project progress management. 'Essential factors of TQM' are arranged 4 items. Quality team's independence and role, goal-setting, Quality Information System, corporate's philosophy of quality first. 'Essential factors of Lean Six Sigma' are the selection of value stream which is based on the customer needs and the value creation and identify the project based on the selected value in the company. 'Essential factors of ERP' are investigated 6 items. Ongoing system maintenance and upgrades, the measurement and support of user satisfaction, the operating systems and the policies for the maintenance, IT infrastructure, change adaption condition monitoring, focusing on improving business performance. 'Essential factors for TPM' are arranged 4 items. Motivated and energetic Bottom-Up, CEO's recognition of the importance facility management, long-term perspective of necessity and ongoing patience. 'Essential factors for BPR' are the pursuit of change process and the staff's sense of crisis management. 'Essential factors for Project Management' are the strategy that reduce the risk management skills through risk management and the understanding and organized management for the project participant's needs. 'Essential factors for System Engineering' consist of 2 items. The first is the design for the best balanced system with pre-analysis about the compromise the cost, schedule and the performance. The second is the analysis of large problem into small problems which can solved. We have found the solution considering components of the interface through the systematic perspective. Conclusion: Common factors and essential factors presented in this study will properly help to introduce the individual management innovation activities for the each business sector and implement management innovation. After this study, new literature research that reflect new studies should accomplish steadily.
KIPS Transactions on Software and Data Engineering
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v.2
no.8
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pp.543-554
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2013
Model-Driven Development(MDD) helps developers verify requirements and design issues of a software system in the early stage of development process by taking advantage of a software model which is the most highly abstracted form of a software system. In practice, however, many software systems have been developed through a code-centric method that builds a software system bottom-up rather than top-down. So, without support of appropriate tools, it is not easy to introduce MDD to real development process. Although there are many researches about extracting a model from code to help developers introduce MDD to code-centrically developed system, most of them only extracted base-level models. However, using concept of abstract component one can continuously extract higher level model from base-level model. In this paper we propose a practical method for automatic extraction of base level abstract component from source code, which is the first stage of continuous extraction process of abstract component, and validate the method by implementing an extraction tool based on the method. Target code chosen is the source code of TinyOS, an operating system for wireless sensor networks. The tool is applied to the source code of TinyOS, written in nesC language.
The benefit that a consumer derives from the use of a good often depends on the number of other consumers purchasing the same goods or other compatible items. This property, which is known as network externality, is significant in many IT related industries. Over the past few decades, network externalities have been recognized in the context of physical networks such as the telephone and railroad industries. Today, as many products are provided as a form of system that consists of compatible components, the appreciation of network externality is becoming increasingly important. Network externalities have been extensively studied among economists who have been seeking to explain new phenomena resulting from rapid advancements in ICT (Information and Communication Technology). As a result of these efforts, a new body of theories for 'New Economy' has been proposed. The theoretical bottom-line argument of such theories is that technologies subject to network effects exhibit multiple equilibriums and will finally lock into a monopoly with one standard cornering the entire market. They emphasize that such "tippiness" is a typical characteristic in such networked markets, describing that multiple incompatible technologies rarely coexist and that the switch to a single, leading standard occurs suddenly. Moreover, it is argued that this standardization process is path dependent, and the ultimate outcome is unpredictable. With incomplete information about other actors' preferences, there can be excess inertia, as consumers only moderately favor the change, and hence are themselves insufficiently motivated to start the bandwagon rolling, but would get on it once it did start to roll. This startup problem can prevent the adoption of any standard at all, even if it is preferred by everyone. Conversely, excess momentum is another possible outcome, for example, if a sponsoring firm uses low prices during early periods of diffusion. The aim of this paper is to analyze the dynamics of the adoption process in markets exhibiting network effects by focusing on two factors; switching and agent heterogeneity. Switching is an important factor that should be considered in analyzing the adoption process. An agent's switching invokes switching by other adopters, which brings about a positive feedback process that can significantly complicate the adoption process. Agent heterogeneity also plays a important role in shaping the early development of the adoption process, which has a significant impact on the later development of the process. The effects of these two factors are analyzed by developing an agent-based simulation model. ABM is a computer-based simulation methodology that can offer many advantages over traditional analytical approaches. The model is designed such that agents have diverse preferences regarding technology and are allowed to switch their previous choice. The simulation results showed that the adoption processes in a market exhibiting networks effects are significantly affected by the distribution of agents and the occurrence of switching. In particular, it is found that both weak heterogeneity and strong network effects cause agents to start to switch early and this plays a role of expediting the emergence of 'lock-in.' When network effects are strong, agents are easily affected by changes in early market shares. This causes agents to switch earlier and in turn speeds up the market's tipping. The same effect is found in the case of highly homogeneous agents. When agents are highly homogeneous, the market starts to tip toward one technology rapidly, and its choice is not always consistent with the populations' initial inclination. Increased volatility and faster lock-in increase the possibility that the market will reach an unexpected outcome. The primary contribution of this study is the elucidation of the role of parameters characterizing the market in the development of the lock-in process, and identification of conditions where such unexpected outcomes happen.
Open Source Software Development (OSSD) differentiates itself from traditional closed software development in that it reveals its source codes online and allows anyone to participate in projects. Even though its success was in doubt, many of the open collaborative working models produced successful results. Academia started to get interested in how developers are willing to participate even when there are no extrinsic rewards for their efforts. Many studies tried to explain developers' motivations, and the pursuit of ideology, reputation, and altruism are found to be the answers. Those studies, however, focused mostly on how the first contribution is made out of a certain motivation. Nowadays, OSSD reaches at its maturity and 70% of professional developers have used or utilized open source software or code in their works. As the proportion of people experiencing OSS, the accounts from previous studies are expected to be weakened. Also, extant literature fails to explain how the motivation of participating in OSS evolves over time and experiences. Given that changing over time or over experiences is the natural in the perception of motivation, studies in an attempt to understand how the motivation changes or evolves are in need. In this study, we aimed to explain how the perception about OSS from past usage or related experiences leads to the intention to sustain OSS participations. By doing so, we try to bridge the gap between previous studies and the actual phenomenon. We argued that perceived instrumentality about OSS learned from past experiences will first affect the formation of organizational identity towards general OSS community. And once the organizational identity is formed, it will affect the one's following behaviors related to OSS development, most likely to sustain the favoring stance toward OSS community. Our research distinguishes itself from previous one in that it divides the paths from organizational identity formed to the intention to sustain the voluntary helping behaviors, by altruistic and conforming intentions. Drawing on this structural model, we could explain how organizational identity engages in forming the sustaining intention from past experiences, and that the intention to help at individual level and organizational level works at different level in OSS community. We grounded our arguments on Social identity theory and Organizational Citizenship theory. We examined our assumption by constructing a structural equation model (SEM) and had 88 developers to answer our online surveys. The result is analyzed by PLS (partial least square) method. Consequently, all paths but one in our model are supported, the one which assumed the association between perceived instrumentality and altruistic intention. Our results provide directions in designing online collaborative platforms where open access collaboration is meant to occur. Theoretically, our study suggests that organizational citizenship behavior can occur from organizational identity, even in bottom-up organizational settings. More specifically, we also argue to consider both organizational level and individual level of motivation in inducing sustained participations within the platforms. Our result can be interpreted to indicate the importance of forming organizational identity in sustaining the participatory behaviors. It is because there was no direct association between perceived instrumentality from past experiences and altruistic behavior, but the perception of organizational identity bridges the two constructs. This means that people with no organizational identity can sustain their participations through conforming intention from only the perception of instrumentality, but it needs little more than that for the people to feel the intention to directly help someone in the community-first to form the self-identity as a member of the given community.
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