• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.433-434
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• 2014

Big Data services is composed of Big Data user, Big Data service provider, and Big Data application provider. And it is possible to extend the service to interplay-reciprocal actions among three subjects such as providing, being provided, connecting, being connected, and so on. In this paper, we propose an ecosystems of Big Data and a framework of its service.

• The Journal of Information Systems
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• v.23 no.4
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• pp.93-117
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• 2014

How can business ecosystems be a source of firm's competitiveness? Is corporate social responsibility (CSR) is an investment activity for building sustainable business ecosystems? The purpose of this research is to identify the relationship between CSR, social value, sustainable business ecosystems, and firm's competitiveness by introducing a mediating role of social capital. We conducted in-depth interviews with seven informants from two domestic firms and four oversea firms. Three propositions were drawn by analyzing qualitative data collected from the interviews and literature review. Various activities creating social value including CSR and CSV (Creating Shared Value) are positively associated with sustainable business ecosystems. Firm accumulates social capital of the business ecosystem through creation of social value. Finally, the social capital of business ecosystem has a positive influence on firm's competitiveness. Implications were suggested for academics and practitioners.

• STI Policy Review
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• v.7 no.2
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• pp.35-59
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• 2016

The strategic importance of innovation ecosystems has received increased attention from both the academic and policy perspectives. However, there is only limited empirical evidence on the importance of these ecosystems from the perspective of younger firms. This study focuses on the role of ecosystems for young innovative companies (YICs) and is based on a unique set of phone survey data from Finland and South Korea. The results are threefold: (1) Finnish YICs participate more actively in ecosystems than Korean YICs; (2) on average, Korean YICs report to have experienced lower ecosystem impact compared to Finnish YICs; (3) in both countries, key organizations of the ecosystems are represented on the board of directors in about one-third of the sample firms.

• The Korean Journal of Ecology
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• v.28 no.6
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• pp.405-415
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• 2005

This paper considers the advantage of Machine Learning (ML) implemented to freshwater ecosystem research. Currently, many studies have been carried out to find the patterns of environmental impact on dynamics of communities in aquatic ecosystems. Ecological models popularly adapted by many researchers have been a means of information processing in dealing with dynamics in various ecosystems. The up-to-date trend in ecological modelling partially turns to the application of ML to explain specific ecological events in complex ecosystems and to overcome the necessity of complicated data manipulation. This paper briefly introduces ML techniques applied to freshwater ecosystems in Korea. The manuscript provides promising information for the ecologists who utilize ML for elucidating complex ecological patterns and undertaking modelling of spatial and temporal dynamics of communities.

• Korean Journal of Environmental Biology
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• v.42 no.2
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• pp.207-218
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• 2024

Food webs have received global attention as next-generation biomonitoring tools; however, it remains challenging because revealing trophic links between species is costly and laborious. Although a link-extrapolation method utilizing published trophic link data can address this difficulty, it has limitations when applied to construct food webs in domestic streams due to the lack of information on endemic species in global literature. Therefore, this study aimed to develop a link extrapolation-based food web model adapted to Korean stream ecosystems. We considered taxonomic similarity of predation and dominance of generalists in aquatic ecosystems, designing taxonomically higher-level matching methods: family matching for all fish (Family), endemic fish (Family-E), endemic fish playing the role of consumers (Family-EC), and resources (Family-ER). By adding the commonly used genus matching method (Genus) to these four matching methods, a total of five matching methods were used to construct 103 domestic food webs. Predictive power of both individual links and food web indices were evaluated by comparing constructed food webs with corresponding empirical food webs. Results showed that, in both evaluations, proposed methods tended to perform better than Genus in a data-poor environment. In particular, Family-E and Family-EC were the most effective matching methods. Our model addressed domestic data scarcity problems when using a link-extrapolation method. It offers opportunities to understand stream ecosystem food webs and may provide novel insights into biomonitoring.

• Korean Journal of Environmental Biology
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• v.21 no.3
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• pp.223-233
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• 2003

This paper introduces a study on the development of environment assessment technique and biodiversity management system for stream ecosystems and their application to Korean streams. Based on comprehensive field investigations from a series of streams of Bukhangang (North Han River) system as well as on long-term field survey and bibliographic data from streams throughout South Korea, schemes for environmental and biodiversity research of stream ecosystems aye reviewed; types of major environmental damages in Korean streams are classified; a rapid assessment technique for nature quality of stream ecosystems is presented; and a list of environmental and biotic factors for the use of GIS-based biodiversity management system in stream ecosystems is provided. The biodiveysity management system, which is based on ArcView and GEUS programs, is applied to Gapyeong Creek, a typical mid-size stream in Korea.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.408-416
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• 2023

The IUCN Red List of Ecosystems serves as a global standard for assessing and identifying ecosystems at high risk of biodiversity loss, providing scientific evidence necessary for effective ecosystem management and conservation policy formulation. The IUCN Red List of Ecosystems has been designated as a key indicator (A.1) for Goal A of the Kunming-Montreal Global Biodiversity Framework. The assessment of the Red List of Ecosystems discerns signs of ecosystem collapse through specific criteria: reduction in distribution (Criterion A), restricted distribution (Criterion B), environmental degradation (Criterion C), changes in biological interaction (Criterion D), and quantitative estimation of the risk of ecosystem collapse (Criterion E). Since 2014, the IUCN Red List of Ecosystems has been evaluated in over 110 countries, with more than 80% of the assessments conducted in terrestrial and inland water ecosystems, among which tropical and subtropical forests are distributed ecosystems under threat. The assessment criteria are concentrated on spatial signs (Criteria A and B), accounting for 68.8%. There are three main considerations for applying the Red List of Ecosystems assessment domestically: First, it is necessary to compile applicable terrestrial ecosystem types within the country. Second, it must be determined whether the spatial sign assessment among the Red List of Ecosystems categories can be applied to the various small-scale ecosystems found domestically. Lastly, the collection of usable time series data (50 years) for assessment must be considered. Based on these considerations, applying the IUCN Red List of Ecosystems assessment domestically would enable an accurate understanding of the current state of the country's unique ecosystem types, contributing to global efforts in ecosystem conservation and restoration.

• The Journal of Information Systems
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• v.24 no.3
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• pp.47-74
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• 2015

Purpose By participating in the business ecosystems, customers make both positive and negative impacts in the ecosystem. In particular, users of platform businesses participate in the business ecosystem as partial employees who voluntarily create and manage content. According to the organizational behavior literature, employees' psychological ownership toward the organization has an influence on the organizational competitiveness. Thus, with an assumption that customers gain psychological ownership toward the business that they participate in, it is important to analyze the process and the factors that influence their psychological ownership. This study proposes a research model that describes the process: customers undertake customer socialization, which then lead them to participate in the business-level and the business ecosystem-level activities. Through the participation, customers gain psychological ownership toward the business. Design/methodology/approach Based on a structural equation model, this study analyzes the data regarding the factors in the research model. Data was collected by surveying college students who represent themselves as Facebook and DaumKakao users. By analyzing the collected data, the relationships are validated between customer socialization and customer participations (i.e., both business-level and business ecosystem-level participation), and between the participations and customers' psychological ownership. Findings Based on the validation, this study confirms the importance of managing customers' psychological ownership and offers customers' participation by their socialization as a solution for increasing customers' psychological ownership. Also, this study proposes the business ecosystem research model as the general research framework for future research and expands the scope of strategic management from the individual level strategy to the business ecosystem wide perspective.

• Journal of Distribution Science
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• v.12 no.12
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• pp.83-92
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• 2014

Purpose - A business ecosystem refers to mutually dependent systems interconnected by a loose foundation of various ecosystem members such as customers, suppliers, partners, and other stakeholders. The ecosystem-based strategy attempts to achieve competitive advantage for firms by enriching a business ecosystem or building a sustainable business ecosystem through the collaboration and co-evolution of its members. A sustainable business ecosystem is a source of competitiveness for firms anda manageable resource for gaining a competitive advantage. Customers represent the core membership of the business ecosystem and play a pivotal role in building a sustainable business ecosystem. This study examines the effects of customer participation on economic and social value in the business ecosystem and suggests a course of action for building a sustainable business ecosystem. Research design, data, and methodology - Two business cases of South Korea are selected from two different business types: business-to-business (B2B) and business-to-customer (B2C) firms. Business ecosystems for B2B and B2C firms reflect contrasting characteristics. Data was collected from in-depth interviews with four representatives of four firms. Results - The study suggested seven propositions for the relationships between customer participation and a sustainable business ecosystem through multiple case studies based on in-depth interviews. The results reveal the following four strategic actions for building sustainable business ecosystems based on the suggested propositions: alignment, systemization, socialization, and co-evolution. Alignment refers to achieving a harmonic balance or virtuous circle among the firm's mission, investment, and value creation. Systemization refers to building and implementing management and infrastructure systems rooted in the corporate culture. Socialization of customers in the business ecosystem reinforces the harmony or virtuous cycle. Finally, co-evolution is associated with the relationship between firms and customers as buyer firms in a restricted business ecosystem. Conclusions - This study considers multiple cases for the execution of a sustainable business ecosystem in collaboration with customers and suggests seven propositions and four strategic actions. The results are based on qualitative data from interviews with business associates from two firms in an open business ecosystem and two firms in a restricted business ecosystem, both in South Korea. Our research results regarding two contrasting business ecosystems shed light on business issues and policy making in Asian business environments, which are in the transition stages from a traditional conglomerate-driven to an inclusive growth-driven economy. The business ecosystem itself should be considered a manageable resource for firms' competitive positions in the market. A customer is a member of the business ecosystem and should thus be viewed not only as a purchasing entity and an object of relationship management but also as a co-creator of value. Therefore, firms should collaborate with customers to build sustainable business ecosystems. For this, firms must create social value, which cannot be created by customers alone, within the business ecosystem. Then, customers participate in a business ecosystem and build it to be favorable to them. Implications for academics and practitioners were suggested.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.5 no.3
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• pp.76-85
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• 2024

The purpose of this study is to propose a new method of analysis focusing on interconnections between species rather than traditional biodiversity analysis, which represents ecosystems in terms of species and individual counts such as species diversity and species richness. This new approach aims to enhance our understanding of ecosystem networks. Utilizing data from the 4th National Natural Environment Survey (2014-2018), the following eight taxonomic groups were targeted for our study: herbaceous plants, woody plants, butterflies, Passeriformes birds, mammals, reptiles & amphibians, freshwater fishes, and benthonic macroinvertebrates. A co-occurrence frequency analysis was conducted using nationwide data collected over five years. As a result, in all eight taxonomic groups, the degree value represented by a linear regression trend line showed a slope of 0.8 and the weighted degree value showed an exponential nonlinear curve trend line with a coefficient of determination (R²) exceeding 0.95. The average value of the clustering coefficient was also around 0.8, reminiscent of well-known social phenomena. Creating a combination set from the species list grouped by temporal information such as survey date and spatial information such as coordinates or grids is an easy approach to discern species distributed regionally and locally. Particularly, grouping by species or taxonomic groups to produce data such as co-occurrence frequency between survey points could allow us to discover spatial similarities based on species present. This analysis could overcome limitations of species data. Since there are no restrictions on time or space, data collected over a short period in a small area and long-term national-scale data can be analyzed through appropriate grouping. The co-occurrence frequency analysis enables us to measure how many species are associated with a single species and the frequency of associations among each species, which will greatly help us understand ecosystems that seem too complex to comprehend. Such connectivity data and graphs generated by the co-occurrence frequency analysis of species are expected to provide a wealth of information and insights not only to researchers, but also to those who observe, manage, and live within ecosystems.