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민간조사학과 개설의 필요성과 성장방향에 대한 질적 연구 (A qualitative Research on Establishment of Department of Private Investigation and Its Future Direction)

  • 조성구;이주락
    • 시큐리티연구
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    • 제28호
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    • pp.181-205
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    • 2011
  • 현재 우리나라에서는 민간조사(Private Investigation)의 도입에 대한 다양한 논의들이 행해지고 있다. 그런데 이러한 논의의 핵심 중 하나가 민간조사원의 교육에 관한 것이다. 민간조사원의 교육은 국민의 생명과 재산의 보호와 관련된 것을 주요 업무로 하고 있기 때문에 일반적인 교육과는 달리 전문성과 윤리성을 강하게 요구한다. 그러므로 민간조사원의 전문성과 윤리성을 뒷받침하기위해 체계적인 교육프로그램이 마련되어져야 한다는 것은 당연하다고 할 수 있다. 그러므로 본 연구에서는 민간조사업 관련자들과의 심층면담을 통해 이들이 민간조사 교육을 대학교육에 포함시키는 방안에 대하여 어떻게 생각하는지를 탐색적으로 조사한 후 수집된 자료를 질적 자료분석 프로그램인 NVivo 2를 활용하여 분석하였다. 연구결과, 민간조사가 필요한 이유로는 국가치안인력의 부족과 경찰이 중요한 사건이 아닐 경우 민원인의 피해에 대해서 적극적으로 개입하지 않는 것, 그리고 공권력을 행사하는 경찰관의 신분으로 민사문제에 개입할 수 없는 것이 가장 큰 이유로 나타났다. 그리고 민간조사학과 개설 필요성으로는 전문교육기관의 부재와 경찰 또는 의뢰인으로부터의 민간 조사에 대한 신뢰성 증대가 가장 큰 것으로 드러났다. 민간조사학과의 전망과 진로방향에 대해 연구 참여자들은 크게 "공인민간조사업법"안의 통과 전과 통과 후로 나뉘어 졌다. 법안의 통과 전은 현재와 같이 민간조사와 유사한 보험회사 조사업무, 외국 민간조사업체, 국내 컨설팅 업체, 경호보안업체로 진출하게 될 것이라고 하였고, 법안이 통과되면 이와 더불어 현재의 경비법인과 같은 민간조사법인이 다수 등장하게 될 것으로 전망하여 법안 통과 시 민간조사학과가 활성화될 것이라 판단하였다.

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경찰 및 경호 관련학과 전공교과목에 대한 Q방법론적 선호도 분석 (A Analysis of Q-methodological Preference Degree about the Subjects on School Curriculum Related to the Police & Security Administration - Centering around the Subject of Study on Gwang Ju and Jeon Nam Region -)

  • 김평수
    • 시큐리티연구
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    • 제28호
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    • pp.33-56
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    • 2011
  • 상본 연구는 광주 전남 지역에서 근무하고 있는 현직경찰관의 견해를 경찰경호 관련학과 전공교과목에 대한 Q방법론적 선호도 분석을 실시하였다. 구체적으로 광주 전남 대학의 경찰행정 및 경호관련학과 전공교과목을 조합하여 27문항을 최종 진술문으로 추출하였으며 교과명이 유사하거나 중복된 교과목은 통합하고 다른 의미를 가진 교과목 간에는 분리 과정을 통해 질문지를 작성한 후 2011년 04월 현재 광주 전남지역에서 경찰관으로 재직 중인 20명을 최초 P-Sample로 선정하였다. 이 과정에서 불성실하게 응답한 6명의 자료를 제외한 14명의 자료를 최종 유효 표본으로 선정하였으며, QUANL. PC 프로그램을 적용 및 주 요인분석(principal component analysis)을 실시하였다. 본 연구에서 경찰경호 2개 영역 모두 분석대상으로 삼는 것은 표본특성 및 전공영역이 다소 상이하므로 이 연구에서는 제1차 연구로서 경찰관만을 대상으로 한 경찰전공 영역 교과목에 국한하여 분석연구를 실시하였다. 따라서 경호영역은 후속연구로서 세밀한 분석을 추가 실시할 계획이다. 이러한 연구절차와 연구과정을 통해 제I, II, III유형의 경찰경호 관련학과 전공교과목 선호도 분석을 실시하였다. 구체적인 결과는 다음과 같다. 제I유형은 형법, 형사소송법, 형사특별법 등의 교과목이 긍정적인 동의를 보였다. 제II유형은 범죄수사학, 구급 및 응급처치, 호신술, 형법, 형사소송법 등이 긍정적인 동의를 보였다. 제III유형은 범죄학개론, 범죄수사학, 형사소송법, 경찰학개론, 경찰윤리 등이 긍정적인 동의를 보였다. 이를 토대로 각 유형 간의 일치항목 즉, 공통된 의견을 다음과 같은 결론으로 도출하였다. 우선 긍정적인 공통된 전공교과목으로는 범죄수사학, 범죄학개론, 경찰윤리, 형사특별법, 형사사법실무, 경찰행정론, 경찰법규실습, 구급 및 응급처치, 호신술, 민법총칙, 행정법 등의 교과목이 현장근무시 경찰관들이 느끼는 현실적이고 실증적인 교과목임을 알 수 있었다.

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지역사회 사회안전망구축과 지역사회결속 및 지방자치단체 신뢰의 관계 (Relation of Social Security Network, Community Unity and Local Government Trust)

  • 김영남;김찬선
    • 시큐리티연구
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    • 제42호
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    • pp.7-36
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    • 2015
  • 본 연구는 지역사회 사회안전망구축과 지역사회결속 및 지방자치단체 신뢰의 관계를 규명하는데 있다. 이 연구는 2014년 8월 15일부터 8월 30일까지 약 15일간 광주지역사회 일반시민들을 모집단으로 선정한 다음 집락무선표집법을 이용하여 총 450부를 배부하여 438명을 표집하였다. 최종분석에 사용된 사례 수는 412명이다. 수집된 자료는 SPSSWIN 18.0을 이용하여 요인분석, 신뢰도분석, 다중회귀분석, 경로분석 등의 방법을 활용하였다. 결론은 다음과 같다. 첫째, 사회안전망구축은 지역사회결속에 영향을 미친다. 즉, 범죄예방설계, 지방자치단체안전교육, 경찰치안서비스가 활성화 될수록 시민들의 지역사회제도에 대한 관심은 높다. 거리CCTV시설, 범죄예방설계, 지방자치단체안전교육이 활성화 될수록 안정감은 높다. 둘째, 사회안전망구축은 지방자치단체 신뢰에 영향을 미친다. 즉, 지역자율방범활동, 범죄예방설계, 지방자치단체안전교육, 경찰치안서비스가 활성화 될수록 정책신뢰, 서비스관리신뢰, 업무성과신뢰는 증가한다. 셋째, 지역사회결속은 지방자치단체 신뢰에 영향을 미친다. 즉, 지역사회제도가 잘 이루어질수록 정책신뢰는 높다. 또한 지역사회제도, 안정감이 잘 이루어질수록 업무성과 신뢰는 높다. 넷째, 사회안전망구축은 지역사회결속과 지방자치단체 신뢰에 직 간접적으로 영향을 미친다. 즉, 사회안전망은 지방자치단체 신뢰에 직접적으로 영향을 미치지만, 매개변수 지역사회결속을 통해서 더욱 높은 영향을 미치는 것으로 나타났다.

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소형 사업장 근로자들의 건강증진 생활양식에 영향을 미치는 요인 (A Study on the Factors Affecting Health Promoting Lifestyles of Workers in the Small Scale Industries)

  • 장용남;이은경;정명수;전선영;김상덕;정재열;장두섭;송용선;이기남
    • 대한예방한의학회지
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    • 제5권1호
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    • pp.10-30
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    • 2001
  • Oriental medicine needs to be armed with theories on health-improvement concept under it and basic data matching its views, in order to participate in the health-improvement service in industrial work places. The Orient medicine health-improvement program defines factors that determine individuals' lifestyle, and provides information and technologies for workers to practice in life. To that end, this research compares and analyzes health-improvement concept and health care, defines relations between individuals' health state and their lifestyle as the basic data needed to perform health-improvement business for workers. 1. The subjects employed for this research is categorized into; by gender, males 52.1% and females 47.9% with no big difference between them; and by age, 20s, 6.1%, 30s. 33.9%, 40s, 34.1%, and 50s, 24.8% with 30-50 accounting for most of it. By marriage status, unmarried represents 7.1%, and married 79.1% with most of them married; by revenue, under one million won represents 3.0%, 1-2 million won 26.4%, 2-2.49 million won 11.2%, above 2.5 million won 11.2%, and 1-2.5 million won a majority. By living location, owned houses represents 65.4%, rented houses 14.7%, monthly-rented 9.5%; and by education, elementary and middle school represent 16.9%, high school and its dropouts 22.6%, and junior college and higher 51.6%, with high school and higher occupying most of the group. 2. By job, office workers and managerial workers represent 12.3%, part-timers 21.0%, manual workers 11.4%, jobless 0.6%, professionals 35.6%, service 0.6%, housewives 8.4%, and equipment/machinery operation/assemblers 10.1%. Of this, jobless and part-timers, totaling three, are dropped from this research. By years worked, 0-3.9 years represents 9.7%, 4-7.9 years 6.7%, 8-14.9 years 18.4%, above 15 years 28.7%, and no respondents 36.5%. 3. The degree of the subjects practicing life-improvement lifestyle, on a scale of 1 to 4, is an average of 2.69, personal relations 3.04, self-realization 2.92, stress management 2.76, nutritional state 2.73, responsibility for health 2.47, and athletic activities 2.18, with personal relations earning the highest points and athletic activities the lowest. As for factors influencing health-improvement lifestyle, there is no significant difference between gender, age, and marriage status. Meanwhile, there is significant difference between revenue, dwelling pattern, education level, etc. That is, higher income-bracket, owned houses, rented houses, monthly-rented houses, and higher-educated, in this order, show higher average in health-enhancement lifestyle. By job, housewives, manual workers, office workers, professionals, equipment/ machinery operation/ assemblers, and part-timers, in this order show higher points, while there is no difference with significance by years worked. 4. Factors that affect health-improvement lifestyle are shown below. Self-realization is influenced by age, marriage status, type of dwellings, and level of education; responsibility for health by type of dwellings; athletic activities by gender and age; nutrition by age, marriage status and type of dwellings; personal relations by marriage status; and stress management by type of dwellings. 5. Areas with high points by job show this: in self-realization, office workers, manual workers, housewives, professionals, equipment/ machinery operation/ assemblers, in this order, show difference with significance; in the area of responsibility for health, manual workers, housewives, equipment/ machinery operation/ assemblers, professionals, office workers and part-timers, in this order, do. In athletic activities, manual workers, housewives, office workers, professionals, equipment/ machinery operation/ assemblers, and part-timers, in this order, show difference with significance; in nutrition, housewives, office workers, manual workers, professionals, equipment/ machinery operation/ assemblers, and part-timers, in this order do; and in stress, housewives, office workers, manual workers, professionals, equipment/ machinery operation/ assemblers, part-timers, in this order do. By years worked, more years showed higher points in the area of responsibility for health and nutrition; in the area of athletic activities, above 15 years, 4-8 years, below 4 years and 8-14 years, in this order, show higher points; and no difference shows in realization, personal relation, and stress area. 6. To look at correlation between overall and divisional health-improvement practice degree, this researcher has analyzed it using Person's correlation coefficient. Self-realization, responsibility for health, athletic activities, nutrition, support for personal relations, and stress management show significant correlation with the sub-divisions, while all health-improvement lifestyle shows significant correlation with the six sub-divisions.

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임질환자(淋疾患者)에 관(關)한 사회의학적(社會醫學的) 연구(硏究) -유병률(有病率), PPNG 및 항균제내성(抗菌劑耐性)을 중심(中心)으로- (Socio-medical Study on Gonorrhoea with Special References of Prevalence, PPNG and Antibiotic Resistance)

  • 이성호;황인담;박영수;고대하
    • Journal of Preventive Medicine and Public Health
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    • 제16권1호
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    • pp.41-50
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    • 1983
  • 성병(性病)의 효과적(效果的)인 관리(管理)를 위해서는 성병인구(性病人口)의 정확(正確)한 파악(把握)과 이에 관련(關聯)된 제요인(諸要因)들에 대(對)한 사회(社會) 의학적(醫學的) 조사(調査)가 선행(先行)되어야 함에도 불구(不拘)하고 한국(韓國)에서는 이에 대(對)한 자료(資料)가 빈약(貧弱)한 실정(實情)이다. 특(特)히 성병중(性病中) 가장 높은 빈도(頻度)인 임질(淋疾)의 경우에도 임상적치료(臨床的治療)에 대(對)한 연구(硏究) 외(外)에는 불과 소수(小數)에 지나지 않고, PPNG에 대(對)해서는 Hernandez, 김등(金等)의 조사(調査) 외(外)에는 그에 대(對)한 자료(資料)가 전무(全無)한 편이다. 본(本) 조사(調査)는 1982년(年) 7월(月)동안 전주시(全州市)와 군산시(群山市)의 유흥업소(遊興業所) 접객부(接客婦) 221명(名)의 사회(社會) 경제적(經濟的) 배경(背景)과 임질유병률(淋疾有病率) 및 PPNG의 분포(分布)에 대(對)해 분석(分析)한 바, 다음과 같은 결과(結果)를 얻었다. 1. 조사대상(調査對象)의 평균연령(平均年齡)은 $26.1{\pm}4.7$세(歲)였다. 2. 이들의 교육수준(敎育水準)은 중학교이상(中學校以上)의 학력자(學歷者)가 전체(全體)의 70.6%였으며, 나머지는 국졸이하(國卒以下) 및 무학력자(無學歷者)였다. 3. 유흥업소(遊興業所) 종사경력(從事經歷)은 평균(平均) $2.4{\pm}1.4$년(年)이었으며, 월수입(月收入)은 $239,592{\pm}90,480$원이었다. 4. 조사대상(調査對象)의 47.5%가 피임(避妊)을 하고 있었으며, 90.5%가 1회이상(回以上)의 인공임신중절(人工妊娠中絶)을 경험(經驗)했으며, 17.2%를 제외(除外)하고는 주(週) 1회이상(回以上) 외박(外泊)을 하는 것으로 나타났다. 5. 221명(名)의 대상중(對象中) 37명(名)이 임질(淋疾)에 나환(羅患)되어 있어 임질유병률(淋疾有病率)은 16.7%였고. 이중 13명(名)이 PPNG로서 35.1%였다. 6. 임질유병률(淋疾有病率) 및 PPNG의 비율(比率)과 비교적(比較的) 유의(有意)한 상관관계(相關關係)를 갖는 것은 성교대상(性交對象)과의 접촉회수(接觸回數), 동거여부(同居與否) 및 교육수준(敎育水準) 등(等)으로 나타났다. 7. 37주(株)의 임균(淋菌)은 대부분(大部分) 다제내성(多劑耐性)을 보였는데, 특(特)히 PPNG는 spectinomycin, cephalothin, gentamicin 외(外)의 거의 모든 항균제(抗菌劑)에 대(對)해 고도(高度)의 내성(耐性)을 보였다.

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국내 MIS 연구에서 구조방정식모형 활용에 관한 메타분석 (A Meta Analysis of Using Structural Equation Model on the Korean MIS Research)

  • 김종기;전진환
    • Asia pacific journal of information systems
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    • 제19권4호
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    • pp.47-75
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    • 2009
  • Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

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

  • 박재성;조용수;고준
    • Asia pacific journal of information systems
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    • 제19권4호
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    • pp.77-100
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    • 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.

A New Item Recommendation Procedure Using Preference Boundary

  • Kim, Hyea-Kyeong;Jang, Moon-Kyoung;Kim, Jae-Kyeong;Cho, Yoon-Ho
    • Asia pacific journal of information systems
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    • 제20권1호
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    • pp.81-99
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    • 2010
  • Lately, in consumers' markets the number of new items is rapidly increasing at an overwhelming rate while consumers have limited access to information about those new products in making a sensible, well-informed purchase. Therefore, item providers and customers need a system which recommends right items to right customers. Also, whenever new items are released, for instance, the recommender system specializing in new items can help item providers locate and identify potential customers. Currently, new items are being added to an existing system without being specially noted to consumers, making it difficult for consumers to identify and evaluate new products introduced in the markets. Most of previous approaches for recommender systems have to rely on the usage history of customers. For new items, this content-based (CB) approach is simply not available for the system to recommend those new items to potential consumers. Although collaborative filtering (CF) approach is not directly applicable to solve the new item problem, it would be a good idea to use the basic principle of CF which identifies similar customers, i,e. neighbors, and recommend items to those customers who have liked the similar items in the past. This research aims to suggest a hybrid recommendation procedure based on the preference boundary of target customer. We suggest the hybrid recommendation procedure using the preference boundary in the feature space for recommending new items only. The basic principle is that if a new item belongs within the preference boundary of a target customer, then it is evaluated to be preferred by the customer. Customers' preferences and characteristics of items including new items are represented in a feature space, and the scope or boundary of the target customer's preference is extended to those of neighbors'. The new item recommendation procedure consists of three steps. The first step is analyzing the profile of items, which are represented as k-dimensional feature values. The second step is to determine the representative point of the target customer's preference boundary, the centroid, based on a personal information set. To determine the centroid of preference boundary of a target customer, three algorithms are developed in this research: one is using the centroid of a target customer only (TC), the other is using centroid of a (dummy) big target customer that is composed of a target customer and his/her neighbors (BC), and another is using centroids of a target customer and his/her neighbors (NC). The third step is to determine the range of the preference boundary, the radius. The suggested algorithm Is using the average distance (AD) between the centroid and all purchased items. We test whether the CF-based approach to determine the centroid of the preference boundary improves the recommendation quality or not. For this purpose, we develop two hybrid algorithms, BC and NC, which use neighbors when deciding centroid of the preference boundary. To test the validity of hybrid algorithms, BC and NC, we developed CB-algorithm, TC, which uses target customers only. We measured effectiveness scores of suggested algorithms and compared them through a series of experiments with a set of real mobile image transaction data. We spilt the period between 1st June 2004 and 31st July and the period between 1st August and 31st August 2004 as a training set and a test set, respectively. The training set Is used to make the preference boundary, and the test set is used to evaluate the performance of the suggested hybrid recommendation procedure. The main aim of this research Is to compare the hybrid recommendation algorithm with the CB algorithm. To evaluate the performance of each algorithm, we compare the purchased new item list in test period with the recommended item list which is recommended by suggested algorithms. So we employ the evaluation metric to hit the ratio for evaluating our algorithms. The hit ratio is defined as the ratio of the hit set size to the recommended set size. The hit set size means the number of success of recommendations in our experiment, and the test set size means the number of purchased items during the test period. Experimental test result shows the hit ratio of BC and NC is bigger than that of TC. This means using neighbors Is more effective to recommend new items. That is hybrid algorithm using CF is more effective when recommending to consumers new items than the algorithm using only CB. The reason of the smaller hit ratio of BC than that of NC is that BC is defined as a dummy or virtual customer who purchased all items of target customers' and neighbors'. That is centroid of BC often shifts from that of TC, so it tends to reflect skewed characters of target customer. So the recommendation algorithm using NC shows the best hit ratio, because NC has sufficient information about target customers and their neighbors without damaging the information about the target customers.

Dynamics of Technology Adoption in Markets Exhibiting Network Effects

  • Hur, Won-Chang
    • Asia pacific journal of information systems
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    • 제20권1호
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    • pp.127-140
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    • 2010
  • The benefit that a consumer derives from the use of a good often depends on the number of other consumers purchasing the same goods or other compatible items. This property, which is known as network externality, is significant in many IT related industries. Over the past few decades, network externalities have been recognized in the context of physical networks such as the telephone and railroad industries. Today, as many products are provided as a form of system that consists of compatible components, the appreciation of network externality is becoming increasingly important. Network externalities have been extensively studied among economists who have been seeking to explain new phenomena resulting from rapid advancements in ICT (Information and Communication Technology). As a result of these efforts, a new body of theories for 'New Economy' has been proposed. The theoretical bottom-line argument of such theories is that technologies subject to network effects exhibit multiple equilibriums and will finally lock into a monopoly with one standard cornering the entire market. They emphasize that such "tippiness" is a typical characteristic in such networked markets, describing that multiple incompatible technologies rarely coexist and that the switch to a single, leading standard occurs suddenly. Moreover, it is argued that this standardization process is path dependent, and the ultimate outcome is unpredictable. With incomplete information about other actors' preferences, there can be excess inertia, as consumers only moderately favor the change, and hence are themselves insufficiently motivated to start the bandwagon rolling, but would get on it once it did start to roll. This startup problem can prevent the adoption of any standard at all, even if it is preferred by everyone. Conversely, excess momentum is another possible outcome, for example, if a sponsoring firm uses low prices during early periods of diffusion. The aim of this paper is to analyze the dynamics of the adoption process in markets exhibiting network effects by focusing on two factors; switching and agent heterogeneity. Switching is an important factor that should be considered in analyzing the adoption process. An agent's switching invokes switching by other adopters, which brings about a positive feedback process that can significantly complicate the adoption process. Agent heterogeneity also plays a important role in shaping the early development of the adoption process, which has a significant impact on the later development of the process. The effects of these two factors are analyzed by developing an agent-based simulation model. ABM is a computer-based simulation methodology that can offer many advantages over traditional analytical approaches. The model is designed such that agents have diverse preferences regarding technology and are allowed to switch their previous choice. The simulation results showed that the adoption processes in a market exhibiting networks effects are significantly affected by the distribution of agents and the occurrence of switching. In particular, it is found that both weak heterogeneity and strong network effects cause agents to start to switch early and this plays a role of expediting the emergence of 'lock-in.' When network effects are strong, agents are easily affected by changes in early market shares. This causes agents to switch earlier and in turn speeds up the market's tipping. The same effect is found in the case of highly homogeneous agents. When agents are highly homogeneous, the market starts to tip toward one technology rapidly, and its choice is not always consistent with the populations' initial inclination. Increased volatility and faster lock-in increase the possibility that the market will reach an unexpected outcome. The primary contribution of this study is the elucidation of the role of parameters characterizing the market in the development of the lock-in process, and identification of conditions where such unexpected outcomes happen.

온라인 주식게시판 정보와 주식시장 활동에 관한 상관관계 연구 (A Study about the Correlation between Information on Stock Message Boards and Stock Market Activity)

  • 김현모;윤호영;소리;박재홍
    • Asia pacific journal of information systems
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    • 제24권4호
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    • pp.559-575
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    • 2014
  • Individual investors are increasingly flocking to message boards to seek, clarify, and exchange information. Businesses like Seekingalpha.com and business magazines like Fortune are evaluating, synthesizing, and reporting the comments made on message boards or blogs. In March of 2012, Yahoo! Finance Message Boards recorded 45 million unique visitors per month followed by AOL Money and Finance (19.8 million), and Google Finance (1.6 million) [McIntyre, 2012]. Previous studies in the finance literature suggest that online communities often provide more accurate information than analyst forecasts [Bagnoli et al., 1999; Clarkson et al., 2006]. Some studies empirically show that the volume of posts in online communities have a positive relationship with market activities (e.g., trading volumes) [Antweiler and Frank, 2004; Bagnoli et al., 1999; Das and Chen, 2007; Tumarkin and Whitelaw, 2001]. The findings indicate that information in online communities does impact investors' investment decisions and trading behaviors. However, research explicating the correlation between information on online communities and stock market activities (e.g., trading volume) is still evolving. Thus, it is important to ask whether a volume of posts on online communities influences trading volumes and whether trading volumes also influence these communities. Online stock message boards offer two different types of information, which can be explained using an economic and a psychological perspective. From a purely economic perspective, one would expect that stock message boards would have a beneficial effect, since they provide timely information at a much lower cost [Bagnoli et al., 1999; Clarkson et al., 2006; Birchler and Butler, 2007]. This indicates that information in stock message boards may provide valuable information investors can use to predict stock market activities and thus may use to make better investment decisions. On the other hand, psychological studies have shown that stock message boards may not necessarily make investors more informed. The related literature argues that confirmation bias causes investors to seek other investors with the same opinions on these stock message boards [Chen and Gu, 2009; Park et al., 2013]. For example, investors may want to share their painful investment experiences with others on stock message boards and are relieved to find they are not alone. In this case, the information on these stock message boards mainly reflects past experience or past information and not valuable and predictable information for market activities. This study thus investigates the two roles of stock message boards-providing valuable information to make future investment decisions or sharing past experiences that reflect mainly investors' painful or boastful stories. If stock message boards do provide valuable information for stock investment decisions, then investors will use this information and thereby influence stock market activities (e.g., trading volume). On the contrary, if investors made investment decisions and visit stock message boards later, they will mainly share their past experiences with others. In this case, past activities in the stock market will influence the stock message boards. These arguments indicate that there is a correlation between information posted on stock message boards and stock market activities. The previous literature has examined the impact of stock sentiments or the number of posts on stock market activities (e.g., trading volume, volatility, stock prices). However, the studies related to stock sentiments found it difficult to obtain significant results. It is not easy to identify useful information among the millions of posts, many of which can be just noise. As a result, the overall sentiments of stock message boards often carry little information for future stock movements [Das and Chen, 2001; Antweiler and Frank, 2004]. This study notes that as a dependent variable, trading volume is more reliable for capturing the effect of stock message board activities. The finance literature argues that trading volume is an indicator of stock price movements [Das et al., 2005; Das and Chen, 2007]. In this regard, this study investigates the correlation between a number of posts (information on stock message boards) and trading volume (stock market activity). We collected about 100,000 messages of 40 companies at KOSPI (Korea Composite Stock Price Index) from Paxnet, the most popular Korean online stock message board. The messages we collected were divided into in-trading and after-trading hours to examine the correlation between the numbers of posts and trading volumes in detail. Also we collected the volume of the stock of the 40 companies. The vector regression analysis and the granger causality test, 3SLS analysis were performed on our panel data sets. We found that the number of posts on online stock message boards is positively related to prior stock trade volume. Also, we found that the impact of the number of posts on stock trading volumes is not statistically significant. Also, we empirically showed the correlation between stock trading volumes and the number of posts on stock message boards. The results of this study contribute to the IS and finance literature in that we identified online stock message board's two roles. Also, this study suggests that stock trading managers should carefully monitor information on stock message boards to understand stock market activities in advance.