• Current Optics and Photonics
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• v.4 no.1
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• pp.69-80
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• 2020

A Rayleigh Lidar used for wind detection works by transmitting laser pulses to the atmosphere and receiving backscattering signals from molecules. Because of the weak backscattering signals, a lidar usually uses a high sensitivity photomultiplier as detector and photon counting technology for signal collection. The capturing of returned extremely weak backscattering signals requires the lidar to work on dark background with a long time accumulation to get high signal-to-noise ratio (SNR). Because of the strong solar background during the day, the SNR of lidar during daytime is much lower than that during nighttime, the altitude and accuracy of detection are also restricted greatly. Therefore this article describes an ultra-narrow bandwidth filter (UNBF) that has been developed on 354.7 nm wavelength of laser. The UNBF is used for suppressing the strong solar background that degrades the performance of Rayleigh wind lidar during daytime. The optical structure of UNBF consists of an interference filter (IF), a low resolution Fabry-Perot interferometer (FPI) and a high resolution FPI. The parameters of each optical component of the UNBF are presented in this article. The transmission curve of the aligned UNBF is measured with a tunable laser. Contrasting the result of with-UNBF and with-IF shows that the solar background received by a Licel transient recorder decreases by 50~100 times and that the SNR with-UNBF was improved by 3 times in the altitude range (35 km to 40 km) compared to with-IF at 10:26 to 10:38 on August 29, 2018. By the SNR comparison at four different times of one day, the ratio-values are larger than 1 over the altitude range (25~50 km) in general, the results illustrate that the SNR with-UNBF is better than that with-IF for Rayleigh Lidar during daytime and they demonstrate the effective improvements of solar background restriction of UNBF.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.175-181
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• 2009

Intelligent Transportation Systems(ITS) enables road users to enhance efficiency of their trips in a variety of traffic conditions. As a significant part of ITS, information communication technology among vehicles and between vehicles and infrastructure has been being developed to upgrade current traffic data collection technology through location-based traffic surveillance systems. A wider and detailed range of traffic data can be acquired with ease by the technology. However, its performance level falls with environmental impediments such as large vehicles, buildings, harsh weather, which often bring about wireless communication failure. For imputation of vehicle trajectory data discontinued by the failure, several potential existing methods were reviewed and a new method to complement them was devised. AIMSUN API(Application Programming Interface) software was utilized to simulate vehicle trajectories data and missing vehicle trajectories data was randomly generated for the verification of the method. The method was proven to yield more accurate and reliable traffic data than the existing ones.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.5-24
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• 2022

The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.57-70
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• 2023

The investigation delved into 457 pieces of scholarly work, encompassing articles, published theses, and dissertations from the National Research Foundation of Korea, spanning the period of the 1997 IMF financial crisis up to 2022. The materials were sourced using terms such as 'angel investment', 'angel investor', and 'angel investment attraction'. The initial phase involved filtering out redundant entries from the preliminary collection of 267 works, leaving aside pieces that didn't pertain directly to angel investment as indicated in their abstracts. The next stage of the analysis involved a more rigorous selection process. Out of 43 papers earmarked in the preceding cut, only 32 were chosen. The criteria for this focused on the exclusion of conference presentations, articles that were either not submitted or inconclusive, and those that duplicated content under different titles. The final selection of 32 papers underwent a thorough systematic literature review. These documents, all pertinent to angel investment in South Korea, were scrutinized under five distinct categories: 1) publication year, 2) themes of research, 3) strategies employed in the studies, 4) participants involved in the research, and 5) methods of research utilized. This meticulous process illuminated the existing landscape of angel investment studies within Korea. Moreover, this study pinpointed gaps in the current body of research, offering guidance on future scholarly directions and proposing social scientific theories to further enrich the field of angel investment studies and analysis also seeks to pinpoint which areas require additional exploration to energize the field of angel investment moving forward. Through a comprehensive review of literature, this research intends to validate the establishment of future research trajectories and pinpoint areas that are currently and relatively underexplored in Korea's angel investment research stream. This study revealed that current research on domestic angel investment is concentrated on several areas: 1) the traits of angel investors, 2) the motivations behind angel investing, 3) startup ventures, 4) relevant institutions and policies, and 5) the various forms of angel investments. It was determined that there is a need to broaden the scope of research to aid in enhancing and stimulating the scale of domestic angel investing. This includes research into performance analysis of angel investments and detailed case studies in the field. Furthermore, the study emphasizes the importance of diversifying research efforts. Instead of solely focusing on specific factors like investment types, startups, accelerators, venture capital, and regulatory frameworks, there is a call for research that explores a variety of associated variables. These include aspects related to crowdfunding and return on investment in the context of angel investing, ensuring a more holistic approach to research in this domain. Specifically, there's a clear need for more detailed studies focusing on the relationships with variables that serve as dependent variables influencing the outcomes of angel investments. Moreover, it's essential to invigorate both qualitative and quantitative research that delves into the theoretical framework from multiple perspectives. This involves analyzing the structure of variables that have an impact on angel investments and the decisions surrounding these investments, thereby enriching the theoretical foundation of this field. Finally, we presented the direction of development for future research by confirming that the effect on the completeness of the business plan is high or low depending on the satisfaction of the entrepreneurs in addition to the components.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.6
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• pp.449-469
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• 2011

This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering during 2010. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) Research trends of thermal and fluid engineering have been surveyed as groups of general thermal and fluid flow, fluid machinery, and new and renewable energy. Various topics were presented in the field of general thermal and fluid flow. Research issues mainly focused on the thermal reliability of axial fan and compressor in the field of fluid machinery. Studies on the design of ground source heat pump systems and solar chemical reactors were executed in the field of new and renewable energy. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics and industrial heat exchangers. Researches on heat transfer characteristics included heat transfer in thermoelectric cooling/power generation systems, combined heat and power systems, carbon nano fluid with PVP, channel filled with metal foam and smoke ventilation in a rescue station of a railroad tunnel. Also the studies on flow boiling of R123/oil mixture in a plain tube bundle and R410A charge amount in an air cooled mini-channel condenser were reported. In the area of industrial heat exchangers, researches on plate heat exchanger, shell and tube heat exchanger, enthalpy exchanger, micro channel PCHE were performed. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics and industrial heat exchangers. Researches on heat transfer characteristics included heat transfer in thermoelectric cooling/power generation systems, combined heat and power systems, carbon nano fluid with PVP, channel filled with metal foam and smoke ventilation in a rescue station of a railroad tunnel. Also the studies on flow boiling of R123/oil mixture in a plain tube bundle and R410A charge amount in an air cooled mini-channel condenser were reported. In the area of industrial heat exchangers, researches on plate heat exchanger, shell and tube heat exchanger, enthalpy exchanger, micro channel PCHE were performed. (3) Refrigeration systems with alternative refrigerants such as hydrocarbons, mixed refrigerants, and CO2 were studied. Performance improvement of refrigeration systems are tried applying various ideas of refrigerant subcooling, dual evaporator with hot gas bypass control and feedforward control. The hybrid solar systems combining the solar collection devices with absorption chillers or compression heat pumps are simulated and studied experimentally as well to improve the understanding and the feasibility for actual applications. (4) Research trend in the field of mechanical building facilities has been found to be mainly focused on field applications rather than performance improvements. Various studies on heating and cooling systems, HVAC facilities, indoor air environments and energy resources were carried to improve the maintenance and management of building service equipments. In the field of heating and cooling systems, papers on a transformer cooling system, a combined heat and power, a slab thermal storage and a heat pump were reported. In the field of HVAC facilities, papers on a cooling load, an ondol and a drying were presented. Also, studies on HVAC systems using unutilized indoor air environments and energy resources such as air curtains, bioviolence, cleanrooms, ventilation, district heating, landfill gas were studied. (5) In the field of architectural environment and energy, studies of various purposes were conducted such as indoor environment, building energy, renewable energy and green building. In particular, renewable energy and building energy-related researches have mainly been studied reflecting the global interest. In addition, many researches which related the domestic green building certification of school building were performed to improve the indoor environment of school.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.131-146
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• 2011

It is becoming more essential than ever for office professionals to become competent in information collection/gathering and problem solving in today's global business society. In particular, office professionals do not only assist simple chores but are also forced to make decisions as quickly and efficiently as possible in problematic situations that can end in either profit or loss to their company. Since office professionals rely heavily on their tacit knowledge to solve problems that arise in everyday business situations, it is truly helpful and efficient to refer to similar business cases from the past and share or reuse such previous business knowledge for better performance results. Case-based reasoning(CBR) is a problem-solving method which utilizes previous similar cases to solve problems. Through CBR, the closest case to the current business situation can be searched and retrieved from the case or knowledge base and can be referred to for a new solution. This reduces the time and resources needed and increase success probability. The main purpose of this study is to design a system called COKRS(Case-based reasoning Office Knowledge Recommender System) and develop a prototype for it. COKRS manages cases and their meta data, accepts key words from the user and searches the casebase for the most similar past case to the input keyword, and communicates with users to collect information about the quality of the case provided and continuously apply the information to update values on the similarity table. Core concepts like system architecture, definition of a case, meta database, similarity table have been introduced, and also an algorithm to retrieve all similar cases from past work history has also been proposed. In this research, a case is best defined as a work experience in office administration. However, defining a case in office administration was not an easy task in reality. We surveyed 10 office professionals in order to get an idea of how to define a case in office administration and found out that in most cases any type of office work is to be recorded digitally and/or non-digitally. Therefore, we have defined a record or document case as for COKRS. Similarity table was composed of items of the result of job analysis for office professionals conducted in a previous research. Values between items of the similarity table were initially set to those from researchers' experiences and literature review. The results of this study could also be utilized in other areas of business for knowledge sharing wherever it is necessary and beneficial to share and learn from past experiences. We expect this research to be a reference for researchers and developers who are in this area or interested in office knowledge recommendation system based on CBR. Focus group interview(FGI) was conducted with ten administrative assistants carefully selected from various areas of business. They were given a chance to try out COKRS in an actual work setting and make some suggestions for future improvement. FGI has identified the user-interface for saving and searching cases for keywords as the most positive aspect of COKRS, and has identified the most urgently needed improvement as transforming tacit knowledge and knowhow into recorded documents more efficiently. Also, the focus group has mentioned that it is essential to secure enough support, encouragement, and reward from the company and promote positive attitude and atmosphere for knowledge sharing for everybody's benefit in the company.

• Journal of Distribution Research
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• v.15 no.1
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• pp.49-71
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• 2010

Franchise businesses in South Korea have contributed to economic growth and job creation, and its growth potential remains very high. However, despite such virtues, domestic franchise businesses face many problems such as the instability of franchisor's business structure and weak financial conditions. To solve these problems, the government enacted legislation and strengthened franchise related laws. However, the strengthening of laws regulating franchisors had many side effects that interrupted the development of the franchise business. For example, legal regulations regarding franchisors have had the effect of suppressing the franchisor's leadership activities (e.g. activities such as the ability to advocate the franchisor's policies and strategies to the franchisees, in order to facilitate change and innovation). One of the main goals of the franchise business is to build cooperation between the franchisor and the franchisee for their combined success. However, franchisees can refuse to follow the franchisor's strategies because of the current state of franchise-related law and government policy. The purpose of this study to explore the effects of franchisor's leadership style on franchisee's commitment in a franchise system. We classified leadership styles according to the path-goal theory (House & Mitchell, 1974), and it was hypothesized and tested that the four leadership styles proposed by the path-goal theory (i.e. directive, supportive, participative and achievement-oriented leadership) have different effects on franchisee's commitment. Another purpose of this study to explore the how the level of franchisee's self-efficacy influences both the franchisor's leadership style and franchisee's commitment in a franchise system. Results of the present study are expected to provide important theoretical and practical implications as to the role of franchisor's leadership style, as restricted by government regulations and the franchisee's self-efficacy, which could be needed to improve the quality of the long-term relationship between the franchisor and franchisee. Quoted by Northouse(2007), one problem regarding the investigation of leadership is that there are almost as many different definitions of leadership as there are people who have tried to define it. But despite the multitude of ways in which leadership has been conceptualized, the following components can be identified as central to the phenomenon: (a) leadership is a process, (b) leadership involves influence, (c) leadership occurs in a group context, and (d) leadership involves goal attainment. Based on these components, in this study leadership is defined as a process whereby franchisor's influences a group of franchisee' to achieve a common goal. Focusing on this definition, the path-goal theory is about how leaders motivate subordinates to accomplish designated goals. Drawing heavily from research on what motivates employees, path-goal theory first appeared in the leadership literature in the early 1970s in the works of Evans (1970), House (1971), House and Dessler (1974), and House and Mitchell (1974). The stated goal of this leadership theory is to enhance employee performance and employee satisfaction by focusing on employee motivation. In brief, path-goal theory is designed to explain how leaders can help subordinates along the path to their goals by selecting specific behaviors that are best suited to subordinates' needs and to the situation in which subordinates are working (Northouse, 2007). House & Mitchell(1974) predicted that although many different leadership behaviors could have been selected to be a part of path-goal theory, this approach has so far examined directive, supportive, participative, and achievement-oriented leadership behaviors. And they suggested that leaders may exhibit any or all of these four styles with various subordinates and in different situations. However, due to restrictive government regulations, franchisors are not in a position to change their leadership style to suit their circumstances. In addition, quoted by Northouse(2007), ssubordinate characteristics determine how a leader's behavior is interpreted by subordinates in a given work context. Many researchers have focused on subordinates' needs for affiliation, preferences for structure, desires for control, and self-perceived level of task ability. In this study, we have focused on the self-perceived level of task ability, namely, the franchisee's self-efficacy. According to Bandura (1977), self-efficacy is chiefly defined as the personal attitude of one's ability to accomplish concrete tasks. Therefore, it is not an indicator of one's actual abilities, but an opinion of the extent of how one can use that ability. Thus, the judgment of maintain franchisee's commitment depends on the situation (e.g., government regulation and policy and leadership style of franchisor) and how it affects one's ability to mobilize resources to deal with the task, so even if people possess the same ability, there may be differences in self-efficacy. Figure 1 illustrates the model investigated in this study. In this model, it was hypothesized that leadership styles would affect the franchisee's commitment, and self-efficacy would moderate the relationship between leadership style and franchisee's commitment. Theoretically, quoted by Northouse(2007), the path-goal approach suggests that leaders need to choose a leadership style that best fits the needs of subordinates and the work they are doing. According to House & Mitchell (1974), the theory predicts that a directive style of leadership is best in situations in which subordinates are dogmatic and authoritarian, the task demands are ambiguous, and the organizational rule and procedures are unclear. In these situations, franchisor's directive leadership complements the work by providing guidance and psychological structure for franchisees. For work that is structured, unsatisfying, or frustrating, path-goal theory suggests that leaders should use a supportive style. Franchisor's Supportive leadership offers a sense of human touch for franchisees engaged in mundane, mechanized activity. Franchisor's participative leadership is considered best when a task is ambiguous because participation gives greater clarity to how certain paths lead to certain goals; it helps subordinates learn what actions leads to what outcome. Furthermore, House & Mitchell(1974) predicts that achievement-oriented leadership is most effective in settings in which subordinates are required to perform ambiguous tasks. Marsh and O'Neill (1984) tested the idea that organizational members' anger and decline in performance is caused by deficiencies in their level of effort and found that self-efficacy promotes accomplishment, decreases stress and negative consequences like depression and emotional instability. Based on the extant empirical findings and theoretical reasoning, we posit positive and strong relationships between the franchisor's leadership styles and the franchisee's commitment. Furthermore, the level of franchisee's self-efficacy was thought to maintain their commitment. The questionnaires sent to participants consisted of the following measures; leadership style was assessed using a 20 item 7-point likert scale developed by Indvik (1985), self-efficacy was assessed using a 24 item 6-point likert scale developed by Bandura (1977), and commitment was assessed using a 6 item 5-point likert scale developed by Morgan & Hunt (1994). Questionnaires were distributed to Korean optical franchisees in Seoul. It took about 20 days to complete the data collection. A total number of 140 questionnaires were returned and complete data were available from 137 respondents. Results of multiple regression analyses testing the relationships between the each of the four styles of leadership shown by the franchisor as independent variables and franchisee's commitment as the dependent variable showed that the relationship between supportive leadership style and commitment ($\beta$=.13, p<.001),and the relationship between participative leadership style and commitment ($\beta$=.07, p<.001)were significant. However, when participants divided into high and low self-efficacy groups, results of multiple regression analyses showed that only the relationship between achievement-oriented leadership style and commitment ($\beta$=.14, p<.001) was significant in the high self-efficacy group. In the low self-efficacy group, the relationship between supportive leadership style and commitment ($\beta$=.17, p<.001),and the relationship between participative leadership style and commitment ($\beta$=.10, p<.001) were significant. The study focused on the franchisee's self-efficacy in order to explore the possibility that regulation, originally intended to protect the franchisee, may not be the most effective method to maintain the relationships in a franchise business. The key results of the data analysis regarding the moderating role of self-efficacy between leadership behavior style as proposed by path-goal and commitment theory were as follows. First, this study proposed that franchisor should apply the appropriate type of leadership behavior to strengthen the franchisees commitment because the results demonstrated that supportive and participative leadership styles by the franchisors have a positive influence on the franchisee's level of commitment. Second, it is desirable for franchisor to validate the franchisee's efforts, since the franchisee's characteristics such as self-efficacy had a substantial, positive effect on the franchisee's commitment as well as being a meaningful moderator between leadership and commitment. Third, the results as a whole imply that the government should provide institutional support, namely to put the franchisor in a position to clearly identify the characteristics of their franchisees and provide reasonable means to administer the franchisees to achieve the company's goal.