• Title/Summary/Keyword: University researchers

Search Result 6,674, Processing Time 0.034 seconds

User-participatory Design Process for School Forests - Focusing on Daegu Padong Elementary School - (이용자 참여형 학교숲 설계에 관한 연구 - 대구 파동초등학교를 대상으로 -)

  • Jung, Tae-Yeol;Kwon, Ji-Hyun
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.45 no.6
    • /
    • pp.50-61
    • /
    • 2017
  • This study devised a user-participatory design process for users to participate directly in the design process and was implemented at Daegu Padong Elementary School. Users of the school forest were divided into four groups: the lower grades, the upper grades, local residents(parents included), and faculty. The methods of this study were image survey, preference survey, card playing, and model playing. Researchers investigated the level of user satisfaction the following year. The specific design process is as follows: First of all, the concept of the school forest was established through audio-visual education for students and image research was conducted through drawing and painting activities entitled 'The School Forest I Want'. Second, in the image survey, a survey of areas and facilities with high frequency use was conducted in the study of the lower grades, the upper grades, local residents, and the faculty. Image cards of spaces and facilities that showed high preference were produced and the cards were placed in four groups on the school lot plan to check the location of place and facilities desired. Based on this, a model and a basic idea were created through consultation with future users. Lastly, the study design was completed. After 1 year from the completion of the school forest, users were again surveyed regarding their satisfaction with use. The importance of this study is as follows: 1) Treating all potential users of a school forest as the subject of design participation, 2) Reasoning out a plan created by the users themselves through consultation and discussion throughout all steps of the design process, 3) Grasping how users utilize a school forest and the type of spaces most preferred via preference survey after completion of the school forest and showing the importance of user participation by showing that spaces preferred by users were similar to those in which experts were also highly interested.

A Study on the Impact Factors of Contents Diffusion in Youtube using Integrated Content Network Analysis (일반영향요인과 댓글기반 콘텐츠 네트워크 분석을 통합한 유튜브(Youtube)상의 콘텐츠 확산 영향요인 연구)

  • Park, Byung Eun;Lim, Gyoo Gun
    • Journal of Intelligence and Information Systems
    • /
    • v.21 no.3
    • /
    • pp.19-36
    • /
    • 2015
  • Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.

An Investigation on Expanding Co-occurrence Criteria in Association Rule Mining (연관규칙 마이닝에서의 동시성 기준 확장에 대한 연구)

  • Kim, Mi-Sung;Kim, Nam-Gyu;Ahn, Jae-Hyeon
    • Journal of Intelligence and Information Systems
    • /
    • v.18 no.1
    • /
    • pp.23-38
    • /
    • 2012
  • There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

The Effects of Virtual Reality Advertisement on Consumer's Intention to Purchase: Focused on Rational and Emotional Responses (가상현실(Virtual Reality) 광고가 소비자 구매의도에 미치는 영향: 이성적인 반응과 감성적인 반응의 통합)

  • Cha, Jae-Yol;Im, Kun-Shin
    • Asia pacific journal of information systems
    • /
    • v.19 no.4
    • /
    • pp.101-124
    • /
    • 2009
  • According to Wikipedia, virtual reality (VR) is defined as a technology that allows a user to interact with a computer-simulated environment. Due to a rapid growth in information technology (IT), the cost of virtual reality has been decreasing while the utility of virtual reality advertisements has dramatically increased. Nevertheless, only a few studies have investigated the effects of virtual reality advertisement on consumer behaviors. Therefore, the objective of this study is to empirically examine the effects of virtual reality advertisement. Compared to traditional online advertisements, virtual reality advertisement enables consumers to experience products realistically over the Internet by providing high media richness, interactivity, and telepresence (Suh and Lee, 2005). Advertisements with high media richness facilitate consumers' understanding of advertised products by providing them with a large amount and a high variety of information on the products. Interactivity also provides consumers with a high level of control over the computer-simulated environment in terms of their abilities to adjust the information according to their individual interests and concerns and to be active rather than passive in their engagement with the information (Pimentel and Teixera, 1994). Through high media richness and interactivity, virtual reality advertisements can generate compelling feelings of "telepresence" (Suh and Lee, 2005). Telepresence is a sense of being there in an environment by means of a communication medium (Steuer, 1992). Virtual reality advertisements enable consumers to create a perceptual illusion of being present and highly engaged in a simulated environment, while they are in reality physically present in another place (Biocca, 1997). Based on the characteristics of virtual reality advertisements, a research model has been proposed to explain consumer responses to the virtual reality advertisements. The proposed model includes two dimensions of consumer responses. One dimension is consumers' rational response, which is based on the Information Processing Theory. Based on the Information Processing Theory, product knowledge and perceived risk are selected as antecedents of intention to purchase. The other dimension is emotional response of consumers, which is based on the Attitude-Structure Theory. Based on the Attitude-Structure Theory, arousal, flow, and positive affect are selected as antecedents of intention to purchase. Because it has been criticized to have investigated only one of the two dimensions of consumer response in prior studies, our research model has been built so as to incorporate both dimensions. Based on the Attitude-Structure Theory, we hypothesized the path of consumers' emotional responses to a virtual reality advertisement: (H1) Arousal by the virtual reality advertisement increases flow; (H2) Flow increases positive affect; and (H3) Positive affect increases intension to purchase. In addition, we hypothesized the path of consumers' rational responses to the virtual reality advertisement based on the Information Processing Theory: (H4) Increased product knowledge through the virtual reality advertisement decreases perceived risk; and (H5) Perceived risk decreases intension to purchase. Based on literature of flow, we additionally hypothesized the relationship between flow and product knowledge: (H6) Flow increases product knowledge. To test the hypotheses, we conducted a free simulation experiment [Fromkin and Streufert, 1976] with 300 people. Subjects were asked to use the virtual reality advertisement of a cellular phone on the Internet and then answer questions about the variables. To check whether subjects fully experienced the virtual reality advertisement, they were asked to answer a quiz about the virtual reality advertisement itself. Responses of 26 subjects were dropped because of their incomplete answers. Responses of 274 subjects were used to test the hypotheses. It was found that all of six hypotheses are accepted. In addition, we found that consumers' emotional response has stronger impact on their intention to purchase than their rational response does. This study sheds much light into practical implications for both IS researchers and managers. First of all, while most of previous research has analyzed only one of the customers' rational and emotional responses, we theoretically incorporated and empirically examined both of the two sides. Second, we empirically showed that mediators such as arousal, flow, positive affect, product knowledge, and perceived risk play an important role between virtual reality advertisement and customer's intention to purchase. In addition, the findings of this study can provide a basis of practical strategies for managers. It was found that consumers' emotional response is stronger than their rational response. This result indicates that advertisements using virtual reality should focus on the emotional side, and that virtual reality can be served as an appropriate advertisement tool for fancy products that require their online advertisements to give an impetus to customers' emotion. Finally, even if this study examined the effects of virtual reality advertisement of cellular phone, its findings could be applied to other products that are suited for virtual experience. However, this research has some limitations. We were unable to control different kinds of consumers and different attributes of products on consumers' intention to purchase. It is, therefore, deemed important for future research to control the consumer and product types for more reliable results. In addition to the consumer and product attributes, other variables could affect consumers' intention to purchase. Thus, the future research needs to find ways t control other variables.

A Study on Users' Resistance toward ERP in the Pre-adoption Context (ERP 도입 전 구성원의 저항)

  • Park, Jae-Sung;Cho, Yong-Soo;Koh, Joon
    • Asia pacific journal of information systems
    • /
    • v.19 no.4
    • /
    • pp.77-100
    • /
    • 2009
  • Information Systems (IS) is an essential tool for any organizations. The last decade has seen an increasing body of knowledge on IS usage. Yet, IS often fails because of its misuse or non-use. In general, decisions regarding the selection of a system, which involve the evaluation of many IS vendors and an enormous initial investment, are made not through the consensus of employees but through the top-down decision making by top managers. In situations where the selected system does not satisfy the needs of the employees, the forced use of the selected IS will only result in their resistance to it. Many organizations have been either integrating dispersed legacy systems such as archipelago or adopting a new ERP (Enterprise Resource Planning) system to enhance employee efficiency. This study examines user resistance prior to the adoption of the selected IS or ERP system. As such, this study identifies the importance of managing organizational resistance that may appear in the pre-adoption context of an integrated IS or ERP system, explores key factors influencing user resistance, and investigates how prior experience with other integrated IS or ERP systems may change the relationship between the affecting factors and user resistance. This study focuses on organizational members' resistance and the affecting factors in the pre-adoption context of an integrated IS or ERP system rather than in the context of an ERP adoption itself or ERP post-adoption. Based on prior literature, this study proposes a research model that considers six key variables, including perceived benefit, system complexity, fitness with existing tasks, attitude toward change, the psychological reactance trait, and perceived IT competence. They are considered as independent variables affecting user resistance toward an integrated IS or ERP system. This study also introduces the concept of prior experience (i.e., whether a user has prior experience with an integrated IS or ERP system) as a moderating variable to examine the impact of perceived benefit and attitude toward change in user resistance. As such, we propose eight hypotheses with respect to the model. For the empirical validation of the hypotheses, we developed relevant instruments for each research variable based on prior literature and surveyed 95 professional researchers and the administrative staff of the Korea Photonics Technology Institute (KOPTI). We examined the organizational characteristics of KOPTI, the reasons behind their adoption of an ERP system, process changes caused by the introduction of the system, and employees' resistance/attitude toward the system at the time of the introduction. The results of the multiple regression analysis suggest that, among the six variables, perceived benefit, complexity, attitude toward change, and the psychological reactance trait significantly influence user resistance. These results further suggest that top management should manage the psychological states of their employees in order to minimize their resistance to the forced IS, even in the new system pre-adoption context. In addition, the moderating variable-prior experience was found to change the strength of the relationship between attitude toward change and system resistance. That is, the effect of attitude toward change in user resistance was significantly stronger in those with prior experience than those with no prior experience. This result implies that those with prior experience should be identified and provided with some type of attitude training or change management programs to minimize their resistance to the adoption of a system. This study contributes to the IS field by providing practical implications for IS practitioners. This study identifies system resistance stimuli of users, focusing on the pre-adoption context in a forced ERP system environment. We have empirically validated the proposed research model by examining several significant factors affecting user resistance against the adoption of an ERP system. In particular, we find a clear and significant role of the moderating variable, prior ERP usage experience, in the relationship between the affecting factors and user resistance. The results of the study suggest the importance of appropriately managing the factors that affect user resistance in organizations that plan to introduce a new ERP system or integrate legacy systems. Moreover, this study offers to practitioners several specific strategies (in particular, the categorization of users by their prior usage experience) for alleviating the resistant behaviors of users in the process of the ERP adoption before a system becomes available to them. Despite the valuable contributions of this study, there are also some limitations which will be discussed in this paper to make the study more complete and consistent.

Bankruptcy Prediction Modeling Using Qualitative Information Based on Big Data Analytics (빅데이터 기반의 정성 정보를 활용한 부도 예측 모형 구축)

  • Jo, Nam-ok;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
    • /
    • v.22 no.2
    • /
    • pp.33-56
    • /
    • 2016
  • Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

The Need for Paradigm Shift in Semantic Similarity and Semantic Relatedness : From Cognitive Semantics Perspective (의미간의 유사도 연구의 패러다임 변화의 필요성-인지 의미론적 관점에서의 고찰)

  • Choi, Youngseok;Park, Jinsoo
    • Journal of Intelligence and Information Systems
    • /
    • v.19 no.1
    • /
    • pp.111-123
    • /
    • 2013
  • Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

A Study of Segmental and Syllabic Intervals of Canonical Babbling and Early Speech

  • Chen, Xiaoxiang;Xiao, Yunnan
    • Cross-Cultural Studies
    • /
    • v.28
    • /
    • pp.115-139
    • /
    • 2012
  • Interval or duration of segments, syllables, words and phrases is an important acoustic feature which influences the naturalness of speech. A number of cross-sectional studies regarding acoustic characteristics of children's speech development found that intervals of segments, syllables, words and phrases tend to change with the growing age. One hypothesis assumed that decreases in intervals would be greater when children were younger and smaller decreases in intervals when older (Thelen,1991), it has been supported by quite a number of researches on the basis of cross-sectional studies (Tingley & Allen,1975; Kent & Forner,1980; Chermak & Schneiderman, 1986), but the other hypothesis predicted that decreases in intervals would be smaller when children were younger and greater decreases in intervals when older (Smith, Kenney & Hussain, 1996). Researchers seem to come up with conflicting postulations and inconsistent results about the change trends concerning intervals of segments, syllables, words and phrases, leaving it as an issue unresolved. Most acoustic investigations of children's speech production have been conducted via cross-sectional designs, which involves studying several groups of children. So far, there are only a few longitudinal studies. This issue needs more longitudinal investigations; moreover, the acoustic measures of the intervals of child speech are hardly available. All former studies focus on word stages excluding the babbling stages especially the canonical babbling stage, but we need to find out when concrete changes of intervals begin to occur and what causes the changes. Therefore, we conducted an acoustic study of interval characteristics of segments and words concerning Canonical Babble ( CB) and early speech in an infant aged from 0;9 to 2;4 acquiring Mandarin Chinese. The current research addresses the following two questions: 1. Whether decreases in interval would be greater when children were younger and smaller when they were older or vice versa? 2. Whether the child speech concerning the acoustic features of interval drifts in the direction of the language they are exposed to? The female infant whose L1 was Southern Mandarin living in Changsha was audio- and video-taped at her home for about one hour almost on a weekly basis during her age range from 0;9 to 2;4 under natural observation by us investigators. The recordings were digitized. Parts of the digitized material were labeled. All the repetitions were excluded. The utterances were extracted from 44 sessions ranging from 30 minutes to one hour. The utterances were divided into segments as well as syllable-sized units. Age stages are 0;9-1;0,1;1-1;5, 1;6-2;0, 2;1-2;4. The subject was a monolingual normal child from parents with a good education. The infant was audio-and video-taped in her home almost every week. The data were digitized, segments and syllables from 44 sessions spanning the transition from babble to speech were transcribed in narrow IPA and coded for analysis. Babble was coded from age 0;9-1;0, and words were coded from 1;0 to 2;4, the data has been checked by two professionally trained persons who majored in phonetics. The present investigation is a longitudinal analysis of some temporal characteristics of the child speech during the age periods of 0;9-1;0, 1;1-1;5, 1;6-2;0, 2;1-2;4. The answer to Research Question 1 is that our results are in agreement with neither of the hypotheses. One hypothesis assumed that decreases in intervals would be greater when children were younger and smaller decreases in intervals when older (Thelen,1991); but the other hypothesis predicted that decreases in intervals would be smaller when children were younger and greater decreases in intervals when older (Smith, Kenney & Hussain, 1996). On the whole, there is a tendency of decrease in segmental and syllabic duration with the growing age, but the changes are not drastic and abrupt. For example, /a/ after /k/ in Table 1 has greater decrease during 1;1-1;5, while /a/ after /p/, /t/ and /w/ has greater decrease during 2;1-2;4. /ka/ has greater decrease during 1;1-1;5, while /ta/ and /na/ has greater decrease during 2;1-2;4.Across the age periods, interval change experiences lots of fluctuation all the time. The answer to Research Question 2 is yes. Babbling stage is a period in which the children's acoustic features of intervals of segments, syllables, words and phrases is shifted in the direction of the language to be learned, babbling and children's speech emergence is greatly influenced by ambient language. The phonetic changes in terms of duration would go on until as late as 10-12 years of age before reaching adult-like levels. Definitely, with the increase of exposure to ambient language, the variation would be less and less until they attain the adult-like competence. Via the analysis of the SPSS 15.0, the decrease of segmental and syllabic intervals across the four age periods proves to be of no significant difference (p>0.05). It means that the change of segmental and syllabic intervals is continuous. It reveals that the process of child speech development is gradual and cumulative.

The Communication Repair Strategy Characteristics According to Communication Breakdown of Elderly Man With Alzheimer's Dementia (알츠하이머 치매 노인의 의사소통 단절에 따른 의사소통 회복전략 특성)

  • Kim, Sun-Young;Park, Hee-June
    • Therapeutic Science for Rehabilitation
    • /
    • v.8 no.4
    • /
    • pp.53-63
    • /
    • 2019
  • Objective : Many communication recovery strategies should be used when communication breakdowns occur for successful communication, however, communication problems increase due to inadequate use of such strategies in older people with dementia. The purpose of this study was to investigate the difference of recovery strategy between dementia and the elderly in conversational discourse. Method : The subjects were eight of Alzheimer's dementia and 10 general elderly. Conversation discourse tasks were conducted face-to-face with the subjects. Communication breakdown and communication recovery strategies were analyzed based on 200 utterances collected in the conversation discourse. Result : First, the AD group had more communication breakdown than the control group, but the recovery rate did not differ between the groups. Second, in the AD group, the nonspecific recovery strategy and the clarification demand strategy were used as the expression strategy. The recovery rate after using expressive strategy was more than 90% in explanation strategy, combined strategy, nonspecific repair strategy, and repetition confirmation strategy. The response strategy used a lot of paraphrase strategy and combined strategies, and the recovery rate after using the response strategy was 100% for the simplification strategy, repeat strategy and gesture strategy. Conclusion : The AD group showed more breakdown of research subjects and breakdown of researchers than control group, and it showed ability to use various expression strategy and response strategy though there was difference in repair rate between communication repair strategy. AD group used nonspecific repair strategy in expression strategy the most and paraphrase strategy in response strategy the most. This shows different characteristic from ordinary elderly people. Therefore, it is necessary to utilize this repair strategy for rehabilitation of AD elderly.

The Tool to Design Sustainable Business Models: A Case Study for the Social Ventures (지속가능한 비즈니스모델 설계 도구: 소셜벤처 사례를 중심으로)

  • Park, JaeWhan;Jeon, Hyejin
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
    • /
    • v.14 no.1
    • /
    • pp.187-198
    • /
    • 2019
  • The purpose of this study is to seek ways of utilizing TLBMC by understanding business model of social ventures that are accompanied by social and environmental as well as economic missions. In order to achieve this, business models from economic, environmental and social perspectives will be analyzed, and we seek to enhance sustainability of social venture entrepreneurs. As the analysis tool, TLBMC(Triple Layered Business Model Canvas) expands upon the business model canvas that is widely utilized and recognizes economical terms. The TLBMC is proposed by Joyce, A., & Paquin, R. L.(2016) to help achieve a holistic view with horizontal and vertical associations. The study tries to overcome limitations of previous studies and observe a variety of economic, environmental, and social perspectives that social ventures should have with the TLBMC. As a result, it has the following implications; Firstly, creating separate social, environmental and economic business model canvas helps a business to have a holistic approach. Secondly, it was found that social venture characteristics of environmental and social perspectives were applied in practice. Lastly, we have established experience data on social venture business model. This study focuses on the opinions, the meanings and the subjective views of the participants. As a result, conclusions are drawn by the researchers ' assertions and has limitations as a research on case studies. However, this study will help people who are preparing or studying social ventures to have economic, environmental, and social perspectives. Also, redefinition of the direction and value of entrepreneurs operating social ventures, such as vision and mission, will help clarify the roles and responsibility of organizations. As a fundamental step for future empirical studies, this study could be the base for social venture business model studies.