The rapid growth of the Internet has increased the amount of transmission of personally identifiable information. At the same time, with new Internet related technologies, organizations are trying to collect and access more personal information than before, which in turn makes individuals concern more about their information privacy. For their successful businesses, organizations have tried to alleviate these concerns in two ways: (1) by offering privacy policies that promise certain level of privacy protection; (2) by offering benefits such as financial gains or convenience. In this paper, we interpret these actions in the context of the information processing theory of motivation. This paper follows Hann et al.(2007)'s methods to analyze Internet users privacy concerns in Korea and tries to compare the findings. Our research objectives are as follows: First, we analyze privacy concern mitigation strategies in the framework of the expectancy theory of motivation. Subsequently, we show how the expectancy theory based framework is linked o the conjoint analysis. We empirically validate the predictions that the means to mitigate privacy concerns are associated with positive valences resulting in an increase in motivational score. In order to accommodate real-life contexts, we investigate these means in trade-off situation, where an organization may only be able to offer partially complete privacy protection and/or promotions and/or convenience, While privacy protection (secondary use, improper access) are associated with positive valences, we also find that financial gains can significantly increase the individuals' motivational score of a website in Korea. One important implication of this empirical analysis is that organizations may possess means to actively manage the privacy concerns of Internet users. Our findings show that privacy policies are valued by users in Korea just as in the US or Singapore. Hence, organizations can capitalize on this, by stating their privacy policy more prominently. Also organizations would better think of strategies or means that may increase online users' willingness to provide personal information. Since financial incentives also significantly increase the individuals' motivational score of website participation, we can quantify the value of website privacy protection in terms of monetary gains. We find that Korean Internet users value the total privacy protection (protection against errors, improper access, and secondary use of personal information) as worthy as KW 25,550, which is about US 28. Having done this conjoint analysis, we next adopt cluster analysis methodology. We identify two distinct segments of Korea's internet users-privacy guardians and information sellers, and convenience seekers. The immediate implication of our study is that firms with online presence must differentiate their services to serve these distinct segments to best meet the needs of segments with differing trade-offs between money and privacy concerns. Information sellers are distinguished from privacy guardians by prior experience of information provision, To the extent that businesses cannot observe an individual's prior experience, they must use indirect methods to induce segmentation by self-selection as suggested in classic economics literature of price discrimination, Businesses could use monetary rewards to attract information sellers to provide personal information. One step forward from the societal trends that emphasize the need of legal protection of information privacy, our study wants to encourage organizations and related authorities to have the viewpoints to consider both importance of privacy protection and the necessity of information trade for the growth of e-commerce.
Volkova Nataliia;Poyasok Tamara;Symonenko Svitlana;Yermak Yuliia;Varina Hanna;Rackovych Anna
International Journal of Computer Science & Network Security
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v.24
no.4
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pp.127-134
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2024
The article highlights the problems of the digitalization of the educational process, which affect the pedagogical cluster and are of a psychological nature. The authors investigate the transformational changes in education in general and the individual beliefs of each subject of the educational process, caused by both the change in the format of learning (distance, mixed), and the use of new technologies (digital, communication). The purpose of the article is to identify the strategic trend of the educational process, which is a synergistic combination of pedagogical methodology and psychological practice and avoiding dialectical opposition of these components of the educational space. At the same time, it should be noted that the introduction of digital technologies in the educational process allows for short-term difficulties, which is a usual phenomenon for innovations in the educational sphere. Consequently, there is a need to differentiate the fundamental problems and temporary shortcomings that are inherent in the new format of learning (pedagogical features). Based on the awareness of this classification, it is necessary to develop psychological techniques that will prevent a negative reaction to the new models of learning and contribute to a painless moral and spiritual adaptation to the realities of the present (psychological characteristics). The methods used in the study are divided into two main groups: general-scientific, which investigates the pedagogical component (synergetic, analysis, structural and typological methods), and general-scientific, which are characterized by psychological direction (dialectics, observation, and comparative analysis). With the help of methods disclosed psychological and pedagogical features of the process of digitalization of education in a mixed learning environment. The result of the study is to develop and carry out methodological constants that will contribute to the synergy for the new pedagogical components (digital technology) and the psychological disposition to their proper use (awareness of the effectiveness of new technologies). So, the digitalization of education has demonstrated its relevance and effectiveness in the pedagogical dimension in the organization of blended and distance learning under the constraints of the COVID-19 pandemic. The task of the psychological cluster is to substantiate the positive aspects of the digitalization of the educational process.
Objective: Agu pigs are indigenous to the Okinawa prefecture, which is the southernmost region of Japan. Agu pigs were exposed to a genetic bottleneck during the 20th century, due to the introduction of European pig breeds. The objective of this study was to elucidate the genetic structure of Agu pigs and to determine their relationships with those of five European breeds, two Chinese breeds and Ryukyu wild boar using microsatellite markers. Methods: A total of 203 DNA samples from 8 pig breeds were used in this study. Genotyping was performed using 21 microsatellite markers distributed across 17 chromosomes. Results: Numbers of effective alleles in Agu pigs were fewer than in European breeds and Ryukyu wild boar. Among domestic pigs, Agu pigs had the lowest heterozygosity (0.423) and highest inbreeding coefficient (FIS = 0.202), indicating a severe loss of heterozygosity in Agu pigs possibly due to inbreeding. Neighbor-joining tree analysis was performed based on Reynolds' genetic distances, which clustered Agu pigs with Duroc pigs. However, principal component analysis revealed a unique genetic position of the Agu pig, and the second principal component separated Agu pigs from all other breeds. Structure analysis with the optimal assumption of seven groups (K = 7) indicated that Agu pigs form an independent cluster from the other breeds. In addition, high and significant FST values (0.235 to 0.413) were identified between Agu pigs and the other breeds. Conclusion: This study revealed a substantial loss of genetic diversity among Agu pigs due to inbreeding. Our data also suggest that Agu pigs have a distinctive genetic structure, although gene flows from European breeds were observed.
Journal of the Economic Geographical Society of Korea
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v.21
no.2
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pp.173-191
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2018
Taking note of growing tendency of academic interests and policy applications with regard to social economy, this study aims to suggest economic geographical agenda for social economy. It is presumed that the orientation of social economy toward pursuing social value will exhibit unique spatial characteristics. Elements containing spatial implications have been identified through a review of hierarchial concepts including social innovation, social economy organization and social enterprise. Three approached are suggested as tools of understanding the spatial context of social economy: spatial characteristics inspiring social entrepreneurship, place-based context of decision-making by social economy organizations, and spaces formulated by interactions between the demand for solving social problems and the supply of economic resources. The investigation of social innovation clusters is required to focus on the differentiated characteristics from normal industrial clusters. It is also suggested that the concept of embeddedness be applied in the search of the essence and elements of social economy's ties with local community.
Objectives: This study was conducted to assess the nutritional status and characteristics related to malnutrition in children less than five years of age in Nghean, Vietnam. Methods: In this study, which was conducted in November 2007, 650 child-mother pairs were selected using a two-stage cluster sampling methodology. A structured questionnaire was then administered to the mothers in their home settings. Anthropometric measurement was then used to determine if children were underweight (weight-for-age), wasting (weight-for-height) and stunting (height-for-age) based on reference data from the National Center for Health Statistics (NCHS)/World Health Organization (WHO). Logistic regression analysis was then used to describe the hierarchical relationships between potential risk factors and malnutrition. Results: The mean Z-scores for weight-for-age, height-for-age and weight-for-height were -1.46 (95% CI=-1.57, -1.35), -1.44 (95% CI=-1.56, -1.32) and -0.71 (95% CI=-0.82, -0.60), respectively. Of the children included in this study, 193 (31.8%) were underweight, 269 (44.3%) were stunting and 72 (11.9%) were wasting. Region of residence, the mother's level of education and occupation, household size, number of children in the family, weight at birth and duration of exclusive breastfeeding were found to be significantly related to malnutrition. Conclusions: The findings of this study indicate that malnutrition is still an important problem among children less than five years of age in Nghean, Vietnam. In addition, maternal, socio-economic and environment factors were found to be significant factors for malnutrition among children under five.
Objectives: Poor complementary feeding practices have consistently contributed to the burden of child undernutrition in Indonesia. This study aimed to estimate the prevalence and predictors of the time of the introduction of solid, semi-solid, and soft foods (ISSSF), minimum dietary diversity (MDD), minimum meal frequency (MMF), and minimum acceptable diet (MAD). Methods: We analyzed 4804 last-born infants aged 6-23 months from the 2017 Indonesia Demographic and Health Survey, which employed multistage cluster random sampling. The outcomes were calculated based on the 2021 World Health Organization/United Nations Children's Fund guidelines. The predictors of the 4 complementary feeding indicators were assessed using multivariate Poisson regression with robust variance adjusting for potential confounders and study design. Results: The prevalence of ISSSF, MDD, MMF, and MAD was 86.1%, 54.3%, 71.8%, and 37.6%, respectively, with younger children less likely to meet 3 out of the 4 outcomes. Parental education, the presence of a birth attendant, and maternal media consumption were among the predictors of MDD and MAD. Children from families with higher income were more likely to meet MDD than those from low-income households (adjusted prevalence ratio [aPR], 1.16; 95% confidence interval [CI], 1.05 to 1.28). Living in an urban area was positively associated with MMF (aPR, 1.09; 95% CI, 1.04 to 1.15) and MAD (aPR, 1.12; 95% CI 1.02 to 1.24). In eastern regions, the prevalence of children achieving MDD and MAD was lower than in those living in Java and Bali. Conclusions: It is crucial that more attention and efforts are made to improve the recommended practices throughout Indonesia, since the prevalence of adequate complementary feeding practices remains low.
This study was to analyze structural equation modeling of organizational culture, human resource management and organization performance in the private security corporation. To attain the goal of the study described above paragraphs, the employee of private security corporation located in Seoul, 2006 year were set as a collected group. Then, using the cluster random sampling method, finally drew out 300 peoples and analyzed 250 peoples in total. The material collection device was the brochure named . The validity of instrument was confirmed by confirmatory factor analysis(CFA) The result of reliability check up was here below; Chronbach' ${\alpha}=.724$. To analyze materials, correlation analysis, CFA, SEM were used as statistic analysis techniques. The conclusion based on above study method and the result of material analysis are follows; First, organizational culture influences on the human resource management. Second, organizational culture influences on the organizational performance. Third, human resource management influences on the organizational performance. Particularly, organizational culture influences indirectly on organizational performance throughout human resource management. Human resource management is very important variable mediating organizational culture and performance.
Focusing on open innovation which is regarded as an important framework for strengthening technological innovation capabilities, in this study empirical analysis is conducted on Korean manufacturing companies, particularly based on the survey results of 149 domestic manufacturing companies that carry out innovation activities in order to identify influence factors for open innovation activities. Analysis on the influence factors of open innovation activities categorized into characteristics of environment, firm-specific characteristics, and characteristics of institutions revealed that characteristics of environment in terms of the degree of market competition and technological changes influence outside-in open innovation activities. Such results suggest that companies respond to increased market competition or technological changes by promoting research and development (R&D) and maintaining or acquiring market competitiveness through introduction of external technology and utilization of external information by means of research collaboration, user innovation, and so on. In terms of firm-specific characteristics, outside-in open innovation activities are influence by R&D personnel, R&D investment, number of international business, export, and openness of corporate culture while inside-out open innovation activities are influenced by characteristics of international organization and CEO's capabilities. In order for companies to strengthen outside-in open innovation activities emphasis on research personnel, R&D input factors such as research funds are necessary whereas to increase inside-out open innovation activities organization solely responsible for international affairs should be established while the CEO needs to focus on open and cooperative entrepreneurship rather than internal technological innovation activities. In terms of characteristics of institutions, outside-in innovation activities are influenced by technological networking whereas inside-out innovation activities are influenced by networking for development of technology and the presence in industrial cluster. This means that the government needs to establish industrial clusters and try to expand technological networking to facilitate open innovation activities.
Park, Do-Hyung;Chung, Jaekwon;Chung, Yeo Jin;Lee, Dongwon
Journal of Intelligence and Information Systems
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v.20
no.4
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pp.1-23
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2014
Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.
Journal of the Korean Society for information Management
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v.33
no.3
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pp.63-83
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2016
As the usage of information resources produced in various media and forms has been increased, the importance of metadata as a tool of information organization to describe the information resources becomes increasingly crucial. The purposes of this study are to analyze and to demonstrate the intellectual structure in the field of metadata through co-word analysis. The data set was collected from the journals which were registered in the Core collection of Web of Science citation database during the period from January 1, 1998 to July 8, 2016. Among them, the bibliographic data from 727 journals was collected using Topic category search with the query word 'metadata'. From 727 journal articles, 410 journals with author keywords were selected and after data preprocessing, 1,137 author keywords were extracted. Finally, a total of 37 final keywords which had more than 6 frequency were selected for analysis. In order to demonstrate the intellectual structure of metadata field, network analysis was conducted. As a result, 2 domains and 9 clusters were derived, and intellectual relations among keywords from metadata field were visualized, and proposed keywords with high global centrality and local centrality. Six clusters from cluster analysis were shown in the map of multidimensional scaling, and the knowledge structure was proposed based on the correlations among each keywords. The results of this study are expected to help to understand the intellectual structure of metadata field through visualization and to guide directions in new approaches of metadata related studies.
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