• Title/Summary/Keyword: decision-making system

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Current Status and Future Prospect of Plant Disease Forecasting System in Korea (우리 나라 식물병 발생예찰의 현황과 전망)

  • Kim, Choong-Hoe
    • Research in Plant Disease
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    • v.8 no.2
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    • pp.84-91
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    • 2002
  • Disease forecasting in Korea was first studied in the Department of Fundamental Research, in the Central Agricultural Technology Institute in Suwon in 1947, where the dispersal of air-borne conidia of blast and brown spot pathogens in rice was examined. Disease forecasting system in Korea is operated based on information obtained from 200 main forecasting plots scattered around country (rice 150, economic crops 50) and 1,403 supplementary observational plots (rice 1,050, others 353) maintained by Korean government. Total number of target crops and diseases in both forecasting plots amount to 30 crops and 104 diseases. Disease development in the forecasting plots is examined by two extension agents specialized in disease forecasting, working in the national Agricul-tural Technology Service Center(ATSC) founded in each city and prefecture. The data obtained by the extension agents are transferred to a central organization, Rural Development Administration (RDA) through an internet-web system for analysis in a nation-wide forecasting program, and forwarded far the Central Forecasting Council consisted of 12 members from administration, university, research institution, meteorology station, and mass media to discuss present situation of disease development and subsequent progress. The council issues a forecasting information message, as a result of analysis, that is announced in public via mass media to 245 agencies including ATSC, who informs to local administration, the related agencies and farmers for implementation of disease control activity. However, in future successful performance of plant disease forecasting system is thought to be securing of excellent extension agents specialized in disease forecasting, elevation of their forecasting ability through continuous trainings, and furnishing of prominent forecasting equipments. Researches in plant disease forecasting in Korea have been concentrated on rice blast, where much information is available, but are substan-tially limited in other diseases. Most of the forecasting researches failed to achieve the continuity of researches on specialized topic, ignoring steady improvement towards practical use. Since disease forecasting loses its value without practicality, more efforts are needed to improve the practicality of the forecasting method in both spatial and temporal aspects. Since significance of disease forecasting is directly related to economic profit, further fore-casting researches should be planned and propelled in relation to fungicide spray scheduling or decision-making of control activities.

A study on the feasibility evaluation technique of urban utility tunnel by using quantitative indexes evaluation and benefit·cost analysis (정량적 지표평가와 비용·편익 분석을 활용한 도심지 공동구의 타당성 평가기법 연구)

  • Lee, Seong-Won;Chung, Jee-Seung;Na, Gwi-Tae;Bang, Myung-Seok;Lee, Joung-Bae
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.21 no.1
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    • pp.61-77
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    • 2019
  • If a new utility tunnel is planned for high density existing urban areas in Korea, a rational decision-making process such as the determination of optimum design capacity by using the feasibility evaluation system based on quantitative evaluation indexes and the economic evaluation is needed. Thus, the previous study presented the important weight of individual higher-level indexes (3 items) and sub-indexes (16 items) through a hierarchy analysis (AHP) for quantitative evaluation index items, considering the characteristics of each urban type. In addition, an economic evaluation method was proposed considering 10 benefit items and 8 cost items by adding 3 new items, including the effects of traffic accidents, noise reduction and socio-economic losses, to the existing items for the benefit cost analysis suitable for urban utility tunnels. This study presented a quantitative feasibility evaluation method using the important weight of 16 sub-index items such as the road management sector, public facilities sector and urban environment sector. Afterwards, the results of quantitative feasibility and economic evaluation were compared and analyzed in 123 main road sections of the Seoul. In addition, a comprehensive evaluation method was proposed by the combination of the two evaluation results. The design capacity optimization program, which will be developed by programming the logic of the quantitative feasibility and economic evaluation system presented in this study, will be utilized in the planning and design phases of urban community zones and will ultimately contribute to the vitalization of urban utility tunnels.

A Study on Way to Revitalize the Service Delivery System in the Hinterland Villages in Non-Urbanized Area (비도시지역 배후마을 서비스전달체계 활성화방안 연구)

  • Haechun Jung;Heeseung Yang
    • Journal of Environmental Impact Assessment
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    • v.32 no.6
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    • pp.533-544
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    • 2023
  • The Ministry of Agriculture, Food and Rural Affairs has been promoting policies to strengthen the functions of rural centers (culture, welfare, economy, education, etc.) and to ensure that services from the centers are delivered to and connected to hinterland villages. For this policy purpose, the rural center revitalization project and the basic living base creation project within the rural development projects are being promoted. However, in the process of carrying out the actual project, as the focus is on strengthening the functions of rural centers, service delivery and connection with hinterland villages are not being actively promoted. therefore, in this study, we analyze the projects previously carried out in Jeoksang-myeon, Muju-gun and the regional status, analyze the reasons why hinterland village services were not connected and activated, and propose a direction for the second phase of the basic living base creation project to be carried out in the future. As a result of analyzing the reasons for the failure of hinterland village services to be activated, problems such as disadvantages in accessing services due to dispersed residence in rural areas and limitations in topographical structure, and the lack of a service delivery system to develop demand in hinterland areas were found to be problems. Improvement measures were derived as follows. First, it is a stepping stone construction plan proposed to overcome topographical limitations. Establish a stepping base that will function as a service intermediate terminal to ensure efficient service delivery. Second, for a rational decision-making structure, we proposed a plan for deploying communication channels that could closely collect local opinions by operating various small-scale communities along with the efficient composition of a resident committee that includes residents of the central and hinterland villages and various classes. Third, it is a virtuous cycle of local manpower training plans that train local residents into professional instructors. We aim to complete a sustainable, resident-led service supply system by nurturing the most important service deliverers, that is, activists, in service delivery.

Measuring the Public Service Quality Using Process Mining: Focusing on N City's Building Licensing Complaint Service (프로세스 마이닝을 이용한 공공서비스의 품질 측정: N시의 건축 인허가 민원 서비스를 중심으로)

  • Lee, Jung Seung
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.35-52
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    • 2019
  • As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.

Development of a Prototype System for Aquaculture Facility Auto Detection Using KOMPSAT-3 Satellite Imagery (KOMPSAT-3 위성영상 기반 양식시설물 자동 검출 프로토타입 시스템 개발)

  • KIM, Do-Ryeong;KIM, Hyeong-Hun;KIM, Woo-Hyeon;RYU, Dong-Ha;GANG, Su-Myung;CHOUNG, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.4
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    • pp.63-75
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    • 2016
  • Aquaculture has historically delivered marine products because the country is surrounded by ocean on three sides. Surveys on production have been conducted recently to systematically manage aquaculture facilities. Based on survey results, pricing controls on marine products has been implemented to stabilize local fishery resources and to ensure minimum income for fishermen. Such surveys on aquaculture facilities depend on manual digitization of aerial photographs each year. These surveys that incorporate manual digitization using high-resolution aerial photographs can accurately evaluate aquaculture with the knowledge of experts, who are aware of each aquaculture facility's characteristics and deployment of those facilities. However, using aerial photographs has monetary and time limitations for monitoring aquaculture resources with different life cycles, and also requires a number of experts. Therefore, in this study, we investigated an automatic prototype system for detecting boundary information and monitoring aquaculture facilities based on satellite images. KOMPSAT-3 (13 Scene), a local high-resolution satellite provided the satellite imagery collected between October and April, a time period in which many aquaculture facilities were operating. The ANN classification method was used for automatic detecting such as cage, longline and buoy type. Furthermore, shape files were generated using a digitizing image processing method that incorporates polygon generation techniques. In this study, our newly developed prototype method detected aquaculture facilities at a rate of 93%. The suggested method overcomes the limits of existing monitoring method using aerial photographs, but also assists experts in detecting aquaculture facilities. Aquaculture facility detection systems must be developed in the future through application of image processing techniques and classification of aquaculture facilities. Such systems will assist in related decision-making through aquaculture facility monitoring.

Structural Relationships among Site Quality of Online Wine Store, Perceived Value, and Online Purchase Intention (온라인 와인매장 사이트 품질, 지각된 가치, 온라인 구매의도 간의 구조적 관계)

  • Han, Su-Jin;Kim, Yoo-Jung;Kang, Sora
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.12
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    • pp.6133-6145
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    • 2013
  • With the increasing number of online wine stores, customers are increasingly seeking to purchase wine online. On the other hand, purchasing wine online is prohibited by law or regulation in Korea. Therefore, customers mainly search for wine information, inquire about wine products, and make a pre-purchase at an online wine store. Online wine stores play important roles in customer's purchase decision-making, and are likely to be a useful wine distribution channel in the near future. Therefore, the aim of this study was to identify the determinants of the online wine purchase intention, and examine the structural relationships between the determinants and online wine purchase intention. The site quality of online wine stores (information quality, system quality, service quality), and perceived value (quality value, price value, emotional value, social value) were selected as the determinants of online wine purchase intention based on literature review. The data was collected from those who had experience using an online wine store to purchase wine, and the data was used to test the proposed research model. The findings showed that the information quality was not related to the perceived value (quality value, price value, emotional value, social value). The system quality was proven to be positively and significantly related to the quality value, price value, and emotional value, whereas it had no impact on the social value. In addition, the service quality was found to affect the perceived value (quality value, price value, emotional and social value). Finally, the results showed that the quality value, emotional value, and social value have a positive impact on the online wine purchase intention, whereas the price quality is not related to the online wine purchase intention. These results are expected to make a contribution to a better understanding of how the quality of online wine stores and the customer's perceived value affect the online wine purchasing intention.

The Effect of Meta-Features of Multiclass Datasets on the Performance of Classification Algorithms (다중 클래스 데이터셋의 메타특징이 판별 알고리즘의 성능에 미치는 영향 연구)

  • Kim, Jeonghun;Kim, Min Yong;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.26 no.1
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    • pp.23-45
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    • 2020
  • Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

Economic Analysis of the Livestock Manure Treatment System Using Life-Cycle Cost Technique (LCC 기법을 통한 가축분뇨처리시설의 경제성 분석)

  • Kim, J.H.;Cho, S.H.;Kwag, J.H.;Choi, D.Y.;Jeong, K.H.;Chung, U.S.;Chung, M.S.;Park, S.K.
    • Journal of Animal Environmental Science
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    • v.17 no.sup
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    • pp.61-68
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    • 2011
  • To assess the total cost with all stages of facilities, the feasibility of Life Cycle Cost (LCC) analysis was examined in this study to estimate the livestock manure treatment system and optimal decision making process. For the economic evaluation, the plant/equipment investment and annual operation cost of four Public Livestock Recycling Facilities, whose treatment capacity is 100 ton piggery manure per day, was compared. The initial cost was in the range of 2,699 million won to 3,202 million won, where T and E methods were highest and lowest, respectively. The annual operation cost was in the level of 378 million to 498 million won, which decreased in the following order : T method > J method > E method > B method. For the LCC analysis, 4.7% of interest rate, 3.13% of inflation rate, and 1.52% of net discount rate was considered by the data received from Bank of Korea and Statics Korea in the period of 2000 to 2009. Also, for the calculation of present value factor, the durable years of civil engineering & construction, machinery and electric instrument was 30 years, 10 years and 15 years, respectively. Based on these consideration, operation cost was in the range of 17,570 won/ton to 20,661 won/ton, and E method (17,570 won/ton) was economical and B method (20,661 won/ton) was non-economical. Though initial cost of T method was higher than that of B method, LCC analysis of T method was lower than that of T method due to the lower operation cost. Therefore, LCC analysis, which considers both initial cost and operation cost, is more reasonable evaluation method than either initial cost or annual operation cost. For the change of LCC analysis according to the uncertainty, the sensitivity analysis was carried out using fluctuation magnitude of discount rate in the period of 2000 to 2009. As a result, LCC analysis evaluated by discount rate was stable for the uncertain factors since the cost leadership did not change even though the sensitivity analysis varied. In summary, the economic evaluation using LCC analysis could be an efficient reference to choose the suitable livestock manure treatment plants. Furthermore, standardization of statement calculation for the actual cost analysis should be conducted and more detailed study is necessary to validate this summary. Therefore, the application of comprehensive technology evaluation, which considers LCC analysis, should contribute in obtaining objectivity and enhancing reliability for the 'Evaluation of Livestock Manure Treatment System and its Technology'.

A Status Analysis for the Standards on Permission of Altering Cultural Heritage's Current State Focusing on the Results of Handling Application Cases on Permission of State-Designated Cultural Heritage (Historic Site) for the Last Five Years (2015~2019) (문화재 현상변경 인·허가 검토기준 마련을 위한 실태분석 연구 - 최근 5년(2015~2019)간 국가지정문화재(사적)의 허가신청 안건 처리결과를 중심으로 -)

  • CHO, Hongseok;SUH, Hyunjung;CHOI, Jisu
    • Korean Journal of Heritage: History & Science
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    • v.54 no.3
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    • pp.24-51
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    • 2021
  • Since June 2006, there have been active efforts to systematize the permission system including the amendment of [Cultural Heritage Protection Act]. Cultural Heritage Administration prepared standards on reviewing each type of cultural heritages(CH) in 2015, promoted a project on the modification of permission standards and showed remarkable performances in quantitative aspects. But as there has been little change for the cases applied for permission, additional studies on policy are required to improve the management efficiency and reduce the citizens'inconvenience. In response, this study aims to identify the actual management status on the current state alteration permission system, and establish practically utilizable reference materials at permission review. While historic sites(HS) constitute a relatively small proportion in state-designated CHs, they are subject to the designation of permission standards. Also, with their location in the downtown area, the application rate is high (51.4%) and the results are commonly utilizable to other types of CH. We constructed a DB based on the minutes of Cultural Heritage Committee(CHC) on HS and categorized similar features in permission handling results. The result of the analysis is as follows. Out of a total of 5,243 cases for permission applied for HS, 1,734 cases of cultural heritage areas(CHA) and 3,509 cases of historic and cultural environment preservation areas(HCEPA) have been applied. CHA has a great proportion of the applications for events and festivals, which are highly related to CHs or representing the local area. There is a high permission rate on applications for the purpose of public service by local governments. Meanwhile, HCEPA has a high proportion of applying for the installation and extension of buildings and facilities at the private level. Thus, negative decisions were made for tall buildings, massed facilities, or suspected scattering of similar acts. Our actual condition analysis has identified a total of 78 types of harmful acts which may influence the preservation of CHs. 31 types in CHA and 37 types in HCEPA are categorized. Especially, 10 common types of permission have been confirmed in both sectors. As a result, it is expected to secure consistency in the permission administration, enhance the management efficiency and improve the public's satisfaction over the regulatory administration by providing practically utilizable reference materials for altering the current state of CH and for decision making on the part of CHC.

How Enduring Product Involvement and Perceived Risk Affect Consumers' Online Merchant Selection Process: The 'Required Trust Level' Perspective (지속적 관여도 및 인지된 위험이 소비자의 온라인 상인선택 프로세스에 미치는 영향에 관한 연구: 요구신뢰 수준 개념을 중심으로)

  • Hong, Il-Yoo B.;Lee, Jung-Min;Cho, Hwi-Hyung
    • Asia pacific journal of information systems
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    • v.22 no.1
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    • pp.29-52
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    • 2012
  • Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

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