This research aims to enhance donor engagement by increasing the transparency of nonprofit donation platforms. Donations are primarily based on social trust, and a lack of transparency on these platforms can significantly reduce donor motivation. To address this issue, the study analyzes the user experience of existing donation platforms, identifies problems, and explores potential improvements. The research began with a literature review to examine the social need for donations and their effectiveness. The findings indicate that donors place a high value on transparency and are less willing to donate when this element is lacking. Specifically, when donors can clearly see how their contributions are being utilized, they experience greater psychological satisfaction and are more likely to continue donating. The study analyzed various platforms to identify issues causing user discomfort and compared elements aimed at enhancing transparency. By employing the KJ affinity method and the Double Diamond process, the study aimed to understand the problem's nature and propose solutions considering the interactions between donors and nonprofits. A key conclusion is the critical importance of making information more accessible and intuitive. The findings suggest that greater transparency can help build donor trust, improve nonprofit efficiency, and contribute to a more robust giving ecosystem. Additionally, platforms with increased transparency facilitate ongoing communication between donors and nonprofits, fostering an environment where donors become more actively engaged in their giving. This strategy is expected to play a vital role in promoting a sustainable culture of giving based on mutual trust.
Won Kyung Kim;Goeun Jung;Dongook Son;Sun-Young Kim
Journal of the Korean Association of Geographic Information Studies
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v.27
no.3
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pp.60-75
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2024
Research on health outcomes of environmental factors has been implemented by multiple and interacting factors, including environmental, socio-demographic, economic, and traffic aspects. There are still significant challenges and limitations in constructing databases for the connections between contributing factors and an integrated approach to environmental health research even though there has been a dramatic increase in data availability and incredible technological advance in data storage and processing. This study emphasizes the necessity of establishing a geospatial data pipeline to analyze the impact of environmental factors on health. It also highlights the difficulties and solutions related to the construction and utilization of a geospatial database. Key challenges include diverse data sources and formats, different spatio-temporal data structures, and coordinate system inconsistencies over time within the same geospatial data. To address these issues, a data pipeline was constructed with pre-processing and post-processing for the data, resulting in refined datasets that could be used for calculating geographic variables. In addition, an AWS-based relational database and shared platform were established to provide an efficient environment for data storage and analysis. Guidelines for each step of the process, including data management and analysis, were developed to enable future researchers to effectively use the data pipeline.
Nowadays, online reviews have become a common word of mouth that many users produce and consume. Posting online reviews is a kind of job that consumers do themselves. Since posting online reviews is not mandatory, it entirely relies on the consumer's voluntary willingness. In this respect, this study aims to describe the motivation for posting online reviews and their behavior processes, such as why online reviewers generate reviews and what types of reviews they create. In this study, we have conducted an in-depth study with 18 participants who have experience in posting reviews. By analyzing interview manuscripts from the grounded theory method approach, we have ultimately presented motivating factors for review posting (mutual reciprocity, material rewards), determinants of review browsing (trust toward review contents, preference for review format), and shadow work (a job that must be done, voluntary data production, consumer's share). We have also proposed the dynamics between core dimensions for theorizing a cycle process of review production and consumption. Our findings could bridge the gap in the existing online review research and offer practical implications for platform companies that need review management.
The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.
Diverse research topics relating to Social Network Services (SNS) such as, social affective factors in relationships among internet users, social capital value of SNS, comparing attributes why users are intending to participate in SNS, user's lifestyle and their preferences, and the exploratory seeking potential of SNS as a social capital need to be focused on. However, these researches that have been undertaken only consider facts at a particular period of the changing computing environment. In accordance with this indispensability, the integrated view on what technical, social and business characteristics and attributes need to be acknowledged. The purpose of this study is to analyze the evolving attributes and characteristics of SNS from Web 1.0 to Mobile web 2.0 through the Web 2.0 and Mobile 1.0 period. Based on the relevant literature, the attributes that drive the changing technological, social and business aspects of SNS have been developed and analyzed. This exploratory study analyzed major attributes and relationships between SNS and users by changing the paradigms which represented each period. It classified and chronicled each period by representing paradigms and deducted the attributes by considering three aspects such as technological, social and business administration. The major findings of this study are, firstly, the web based computing environment has been changed into the platform attribute for users in the aspect of technology. Users can only read, listen and view information through the web site in the early stages, but now it is possible that users can create, modify and distribute all kinds of information. Secondly, the few knowledge producers of web services have been changed into a collective intelligence by groups of people in the aspect of society. Information authority has been distributed and there is no limit to its spread. Many businesses recognized the potential of the SNS and they are considering how to utilize these advantages toward channel of promotion and marketing. Thirdly, the conventional marketing channel has been changed into oral transmission by using SNS. The market of innovative mobile technology such as smart phones, which provide convenience and access-ability toward customers, has been enlarged. New opportunities to build friendly relationship between business and customers as a new marketing chance have been created. Finally, the role of the consumer has been changed into the leading role of a prosumer. Users can create, modify and distribute information, and are performing the dual role of customer and producer.
Agrobacterium tumefaciens-mediated transformation(ATMT) of Flammulina velutipes was used to produce a diverse number of transformants to discover the functions of gene that is vital for its variation color, spore pattern and cellulolytic activity. Futhermore, the transformant pool will be used as a good genetic resource for studying gene functions. Agrobacterium-mediated transformation was conducted in order to generate intentional mutants of F. velutipes strain KACC42777. Then Agrobacterium tumefaciens AGL-1 harboring pBGgHg was transformed into F. velutipes. This method is use to determine the functional gene of F. velutipes. Inverse PCR was used to insert T-DNA into the tagged chromosomal DNA segments and conducting sequence analysis of the F. velutipes. But this experiment had trouble in diverse morphological mutants because of dikaryotic nature of mushroom. It needed to make monokaryotic fruiting varients which introduced genes of compatible mating types. In this study, next generation sequencing data was generated from 28 strains of Flammulina velutipes with different phenotypes using Illumina Hiseq platform. Filtered short reads were initially aligned to the reference genome (KACC42780) to construct a SNP matrix. And then we built a phylogenetic tree based on the validated SNPs. The inferred tree represented that white- and brown- fruitbody forming strains were generally separated although three brown strains, 4103, 4028, and 4195, were grouped with white ones. This topological relationship was consistently reappeared even when we used randomly selected SNPs. Group I containing 4062, 4148, and 4195 strains and group II containing 4188, 4190, and 4194 strains formed early-divergent lineages with robust nodal supports, suggesting that they are independent groups from the members in main clades. To elucidate the distinction between white-fruitbody forming strains isolated from Korea and Japan, phylogenetic analysis was performed using their SNP data with group I members as outgroup. However, no significant genetic variation was noticed in this study. A total of 28 strains of Flammulina velutipes were analyzed to identify the genomic regions responsible for producing white-fruiting body. NGS data was yielded by using Illumina Hiseq platform. Short reads were filtered by quality score and read length were mapped on the reference genome (KACC42780). Between the white- and brown fruitbody forming strains. There is a high possibility that SNPs can be detected among the white strains as homozygous because white phenotype is recessive in F. velutipes. Thus, we constructed SNP matrix within 8 white strains. SNPs discovered between mono3 and mono19, the parental monokaryotic strains of 4210 strain (white), were excluded from the candidate. If the genotypes of SNPs detected between white and brown strains were identical with those in mono3 and mono19 strains, they were included in candidate as a priority. As a result, if more than 5 candidates SNPs were localized in single gene, we regarded as they are possibly related to the white color. In F. velutipes genome, chr01, chr04, chr07,chr11 regions were identified to be associated with white fruitbody forming. White and Brown Fruitbody strains can be used as an identification marker for F. veluipes. We can develop some molecular markers to identify colored strains and discriminate national white varieties against Japanese ones.
Most brachytherapy treatment planning systems employ a dosimetry formalism based on the AAPM TG-43 report which does not appropriately consider tissue heterogeneity. In this study we aimed to set up a simple Monte Carlo-based intracavitary high-dose-rate brachytherapy (IC-HDRB) plan verification platform, focusing particularly on the robustness of the direct Monte Carlo dose calculation using material and density information derived from CT images. CT images of slab phantoms and a uterine cervical cancer patient were used for brachytherapy plans based on the Plato (Nucletron, Netherlands) brachytherapy planning system. Monte Carlo simulations were implemented using the parameters from the Plato system and compared with the EBT film dosimetry and conventional dose computations. EGSnrc based DOSXYZnrc code was used for Monte Carlo simulations. Each $^{192}Ir$ source of the afterloader was approximately modeled as a parallel-piped shape inside the converted CT data set whose voxel size was $2{\times}2{\times}2\;mm^3$. Bracytherapy dose calculations based on the TG-43 showed good agreement with the Monte Carlo results in a homogeneous media whose density was close to water, but there were significant errors in high-density materials. For a patient case, A and B point dose differences were less than 3%, while the mean dose discrepancy was as much as 5%. Conventional dose computation methods might underdose the targets by not accounting for the effects of high-density materials. The proposed platform was shown to be feasible and to have good dose calculation accuracy. One should be careful when confirming the plan using a conventional brachytherapy dose computation method, and moreover, an independent dose verification system as developed in this study might be helpful.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.15
no.2
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pp.1-18
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2020
This study is to identify the influence of major variables that affect the participation intention of securities type crowdfunding investors and how participation intention and perceived behavioral control affect investors' herd behavior including indirect effect analysis based on the theory of planned behavior. The ultimate purpose of this study is to understand the investment behavior of securities type crowdfunding investors and to help the relevant parties to develop various policies and business plans to revitalize the system and protect investors. An online survey was conducted on people who are interested or have experience in securities type crowdfunding to receive a total of 276 responses. Excluding outliers, a total of 261 responses were taken into account for the final analysis. For the data analysis, structural equation model analysis using SPSS 22.0 and Amos 22.0 statistical package was conducted. As a result, two of the major variables of the theory of planned behavior-attitude and subjective norm-have been found to have a positive effect on the participation intention of securities type crowdfunding investors. And after analyzing the indirect effect, the participation intention was found to play a mediating role between attitude, subjective norm and herd behavior. However, the perceived behavioral control presented as a major variable of behavioral intention in the theory of planned behavior showed that the effect on participation intention was statistically insignificant. Instead, it was found to have a direct positive effect on herd behavior. This is significant because it empirically confirmed that even if investors perceive securities type crowdfunding as easy to participate, perceived behavioral control does not seem to have a significant impact on participation intention because securities type crowdfunding is an investment in an early-stage business with a high risk of loss. On the other hand, the study has great significance in that it empirically confirmed that domestic securities type crowdfunding investors perceive the funding progress information provided by the platform as a signal and imitate many other investors, showing herd behavior when they actually make an investment. It is expected that this study will provide meaningful insights for the policy making of crowdfunding supervisory offices and platform operators by empirically identifying major variables that influence the participation intentions and herd behavior of domestic securities type crowdfunding investors.
It is desirable to invest in wine that increases its value, but wine investment itself is unfamiliar in Korea. Also, the process itself is unreasonable, and information is often forged, because pricing in the wine market is done by a small number of people. With the right solution, however, the wine market can be a desirable investment destination in that the longer one invests, the higher one can expect. Also, it is expected that the domestic wine consumption market will expand through the steady increase in domestic wine imports. This study presents the consortium block chain framework for revitalizing the wine market and enhancing transparency as the "right solution" of the nation's wine investment market. Blockchain governance can compensate for the shortcomings of the wine market because it guarantees desirable decision-making rights and accountability. Because the data stored in the block chain can be checked by consumers, it reduces the likelihood of counterfeit wine appearing and complements the process of unreasonably priced. In addition, digitization of assets resolves low cash liquidity and saves money and time throughout the supply chain through smart contracts, lowering entry barriers to wine investment. In particular, if the governance of the block chain is composed of 'chateau-distributor-investor' through consortium blockchains, it can create a desirable wine market. The production process is stored in the block chain to secure production costs, set a reasonable launch price, and efficiently operate the distribution system by storing the distribution process in the block chain, and forecast the amount of orders for futures trading. Finally, investors make rational decisions by viewing all of these data. The study presented a new perspective on alternative investment in that ownership can be treated like a share. We also look forward to the simplification of food import procedures and the formation of trust within the wine industry by presenting a framework for wine-owned sales. In future studies, we would like to expand the framework to study the areas to be applied.
his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.
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