• Title/Summary/Keyword: 모형 매개변수

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The Relationship with Electronic Trust, Web Site Commitment and Service Transaction Intention in Public Shipping B2B e-marketplace (해운 B2B e-marketplace의 전자적 신뢰, 사이트몰입 및 서비스 거래의도와의 관계성)

  • Kim, Yong-Man;Kim, Seog-Yong;Lee, Jong-Hwan;Shim, Gyu-Yeol
    • Journal of Global Scholars of Marketing Science
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    • v.17 no.4
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    • pp.113-139
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    • 2007
  • This study aims to, looking from a standpoint of network, has investigated the shipping industry's B2B e-marketplace, the characteristics that can earn electronic trust from the users, and characteristics of the web-site. It has examined the mechanism whereby electronic trust be earned and how it affects web-site involvement and service transaction intention. Ultimately, The study attempts to make proposals whereby such trust can lead for a cooperative trading community in the shipping industry's B2B e-marketplace The Covalence structural equation modeling was designed and empirically tested for the shipping industry's B2B e-marketplace. The shipping industry employees were given questionnaires and data were analyzed. Except for perceived security of the three characteristic factors on the web-site, the perceived site quality and characteristics factors in operation only affected co-variables. Transaction Fairness was determined to be the most important factor among exogenous factors increasing electronic trust. With regards to transaction rules, if a transaction is beneficial only to one side, then no long term transaction will not take place. If the concerned parties properly recognize that transaction fairness is crucial to electronic transaction, then it will enormously contribute to successful operations of shipping e-marketplace. Also, Perceived efficiency in transaction also affects electronic trust. This reduces transaction costs and speeds up and simplifies the transaction process. It has reduced greater time and costs than existing off-line transaction, and would positively affect electronic trust. By making an open forum for participants to obtain information for transaction, they can gather useful information, and at the same time, the web-site operator can provide information, which, in turn, will increase electronic trust in electronic transaction. Furthermore, such formation of trust in electronic transaction influences shipping companies in such a way that they will want to continuously participate in the transaction, raising web-site involvement. The result of increased trust is that shipping companies in the future will do business with each other and form a foundation for continuous transactions amongst themselves. Consequently, the formation of trust in electronic transaction greatly influences web-site involvement and service transaction intention. The results of the study have again proved that in order to maintain continuous business relationship with the current clients, electronic trust in virtual space, which operates the shipping industry's B2B e-marketplace, is important for the interested parties.

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The Impact of Self-efficacy on Job Engagement and Job Performance of SMEs' Members: SEM-ANN Analysis (중소기업 조직구성원의 자기효능감이 직무열의와 직무성과에 미치는 영향: 구조모형분석-인공신경망 분석의 적용)

  • Kang, Tae-Won;Lee, Yong-Ki;Lee, Yong-Suk
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.13 no.6
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    • pp.155-166
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    • 2018
  • The purpose of this study is to analyze the impact of self-efficacy of SMEs' organization members on job engagement and job performance, and to analyze the difference between gender and marital status by applying SEM-ANN analysis. To accomplish the study purpose, 285 valid samples were collected from 400 SMEs' organization members and analyzed. In this study, self - efficacy consisted of three sub-dimensions: self-confidence, self-regulation efficacy, and task difficulty preference. As a result of the analysis, self - efficacy such as self-confidence, self-regulation efficacy, and task difficulty preference had a positive direct effect on job engagement. In addition, self-efficacy and self-control efficacy have a positive effect on job performance, but the preference of task difficulty has no significant effect. In addition, job engagement has a positive(+) effect on job performance, and has a mediating role in the relationship between self-efficacy and job performance. Also, married males preferred self-regulation efficacy, while females preferred self-regulation and self-control efficacy regardless of marital status. The purpose of this study is to present the framework of self-efficacy-job engagement-job performance of SMEs by measuring the self-efficacy related researches mainly in education and service industries, and is meaningful that companies can help to find the basis of management of organization members by gender and marital status of organization members. In addition, the SEM-ANN analysis process of this study is different in that it explains the nonlinear (nonobservative) relationship that can analyze the influence or the combination of the reference variables in the linear (compensatory) relation using the SEM.

A Study on Changes in Consumption Behavior due to the Risk of the COVID-19 Pandemic (COVID-19 팬데믹 위험으로 인한 소비행동의 변화 연구)

  • Oh, Jong-chul;Lee, Yu-sun;Kim, Jae-hong
    • Journal of Venture Innovation
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    • v.5 no.2
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    • pp.49-66
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    • 2022
  • This study intends to examine how the perception of covid-19 risk affects consumers' consumption behavior based on previous studies in a situation where the spread of covid-19 is prolonged. This study demonstrates how consumers' perception of covid-19 risk affects online and offline consumption behavior through the perceived severity, perceived vulnerability, coping effectiveness, and self-efficacy of the revised protective motivation theory (Rogers, 1983). We want to test it through analysis. In order to achieve the purpose of this study, consumers living in Seoul and Gyeonggi Province who have purchased within the past 3 months were selected as a sample. In addition, variable data such as risk perception of covid-19, perceived severity, perceived vulnerability, coping effectiveness, self-efficacy, online purchase attitude and purchase intention, offline purchase attitude and purchase intention were collected through the questionnaire.A total of 363 copies of valid responses were tested to test the hypothesis of the relationship between variables through the covariance structure model. The analysis results of this study were first, that covid-19 risk perception had a significant positive (+) effect on perceived severity, perceived vulnerability, and coping effectiveness. Second, perceived severity and perceived vulnerability were found to have a significant positive (+) effect on offline purchasing attitude. Third, perceived severity, perceived vulnerability, coping plan effectiveness, and self-efficacy were all found to have significant positive (+) effects on online purchase attitude. Finally, it was found that offline purchase attitude and online purchase attitude had a significant positive (+) effect on offline purchase intention and online purchase intention, respectively. Also, it was found that online purchase attitude had a negative (-) effect on offline purchase intention. The results of this analysis will provide meaningful implications for the establishment of strategies for distribution channels according to the social risk of infectious diseases.

A Study on the Effect of SMEs' Organizational Culture and Self-Efficacy on Job Crafting and Job Satisfaction (소기업의 조직문화와 자기효능감이 잡 크래프팅과 직무만족도에 미치는 영향에 관한 연구)

  • Bae, Keun Soo;Heo, Ghul Moo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.5
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    • pp.109-124
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    • 2021
  • This study tried to verify the causal relationship that SMEs' organizational culture and self-efficacy would affect job crafting and job satisfaction. Unlike previous domestic studies that have been studied for organizational culture at the organizational level and self-efficacy at the individual level, this study tried to verify the interaction between job crafting and job satisfaction using different mechanisms as antecedent factors. In order to verify the research model of this study, questionnaires of 144 small and medium-sized enterprises (SMEs) workers located in Seoul and metropolitan areas were analyzed. Factor analysis and correlation analysis were performed to verify the reliability and validity of the research model on the relationship between variables, and empirical analysis was performed using regression analysis and mediation effect analysis to verify the hypothesis. The results of the study were first, that organizational culture and self-efficacy had a positive (+) effect on job crafting. On the other hand, relationship-oriented culture and hierarchical-oriented culture, which are sub-factors of organizational culture, were found to be insignificant. Second, organizational culture and self-efficacy were found to have a positive (+) effect on job satisfaction. On the other hand, it was found that market-oriented culture and hierarchical-oriented culture, which are sub-factors of organizational culture, were not significant. Third, job crafting was found to have a positive (+) effect on job satisfaction. On the other hand, it was found that the sub-factors of job crafting, disruptive job demands and social job resources, were not significant. This means that organizational culture partially affects job crafting and job satisfaction of SMEs, and job crafting also partially affects job satisfaction. The implications of this study are first, suggesting the meaning of SME organizational culture for stable and efficient human resource management for SMEs suffering from low productivity and high turnover rate. Second, it was meaningful to understand the possibility of introducing job crafting as an effective job management plan for SMEs. Third, in the current situation where there are few cases of practical introduction of job crafting, research on understanding job crafting for SMEs and improving job satisfaction is thought to be helpful in improving the productivity of SMEs.

Associations of Communication Skills, Self-Efficacy on Clinical Performance and Empathy in Trainee Doctors (전공의 의료커뮤니케이션 능력과 진료수행 자기효능감, 공감능력과의 상관관계)

  • Kim, Doehyung;Kim, Min-Jeong;Lee, Haeyoung;Kim, Hyunseuk;Kim, Youngmi;Lee, Sang-Shin
    • Korean Journal of Psychosomatic Medicine
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    • v.29 no.1
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    • pp.49-57
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    • 2021
  • Objectives : This study evaluated the medical communication skills of trainee doctors and analyzed the relationship between medical communication skills, self-efficacy on clinical performance (SECP) and empathy. Methods : A total of 106 trainee doctors from a university hospital participated. The questionnaire comprised self-evaluated medical communication skills, modified SECP and the Korean version of the Jefferson Scale of Empathy-Health Professionals version. The mean difference in medical communication skills scores according to gender, age, division (intern, internal medicine group or surgery group) and position (intern, first-/second- and third-/fourth-year residents) were analyzed. Pearson correlation coefficients were determined between medical communication skills, modified SECP and empathy. The effects of each variable on medical communication skills were verified using the structural equation model. Results : There were no statistically significant mean differences in self-evaluated medical communication skills according to gender, age, division or position. Medical communication skills had a significant positive correlation with modified SECP (r=0.782, p<0.001) and empathy (r=0.210, p=0.038). Empathy had a direct effect on modified SECP (β=0.30, p<0.01) and modified SECP had a direct effect on medical communication skills (β=0.80, p<0.001). Empathy indirectly influenced medical communication skills, mediating modified SECP (β=0.26, p<0.05). Conclusions : Medical communication skills are an important core curriculum of residency programs, as they have a direct correlation with SECP, which is needed for successful treatment. Moreover, the medical communication needs a new understanding that is out of empathy.

The Effect of Technology Start-up Companies' Absorption Capacity on Start-up Performance: Focusing on the Mediating Effect of Patent Activities (기술창업기업의 흡수역량이 창업성과에 미치는 영향: 특허활동의 매개효과를 중심으로)

  • Kim Jong Sik;Nam Jung Min
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.3
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    • pp.191-209
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    • 2023
  • Amid rapid changes in technological innovation due to the influence of the 4th Industrial Revolution and COVID-19, research related to absorption capacity and patent activities to promote technological innovation of Korean technology start-ups is important in this uncertain environment. This study aims to examine the effects on entrepreneurial performance and patent activities by reconstructing absorptive capacity, an organizational capability, for technology-based startups in fields such as BT and ICT with less than seven years of establishment, distinguishing between potential absorptive capacity and realized absorptive capacity. The study also seeks to develop a theoretical research model. To accomplish this, data was collected from managerial executives, including CEOs of 215 technology startups. The following hypotheses were tested: Firstly, potential absorptive capacity had a significant impact on patent activities, while realized absorptive capacity did not. Secondly, potential absorptive capacity had a significant impact on technological performance, while realized absorptive capacity did not. Thirdly, both potential and realized absorptive capacity had a significant impact on financial and non-financial performance. Fourthly, patent activities indirectly influenced potential absorptive capacity and technological performance, but did not affect realized absorptive capacity. Fifthly, patent activities indirectly influenced potential absorptive capacity and financial performance, but did not affect realized absorptive capacity. Lastly, patent activities indirectly influenced potential absorptive capacity and non-financial performance, but did not affect realized absorptive capacity. The practical significance of this study lies in providing useful guidelines for building the core capabilities of organizations through absorptive capacity and patent activities. Furthermore, it is expected that startups that have not recognized the formation process of absorptive capacity for patent activities will perceive the formation mechanism of absorptive capability anew and show considerable interest in future potential and realized absorptive capacity as part of their management strategies. This is anticipated to play an important role in adapting to rapidly changing technological advancements, the startup ecosystem, and securing sustainable competitive advantages.

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Sentiment Analysis of Movie Review Using Integrated CNN-LSTM Mode (CNN-LSTM 조합모델을 이용한 영화리뷰 감성분석)

  • Park, Ho-yeon;Kim, Kyoung-jae
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.141-154
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    • 2019
  • Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

A Study on the Effect of Booth Recommendation System on Exhibition Visitors Unplanned Visit Behavior (전시장 참관객의 계획되지 않은 방문행동에 있어서 부스추천시스템의 영향에 대한 연구)

  • Chung, Nam-Ho;Kim, Jae-Kyung
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.175-191
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    • 2011
  • With the MICE(Meeting, Incentive travel, Convention, Exhibition) industry coming into the spotlight, there has been a growing interest in the domestic exhibition industry. Accordingly, in Korea, various studies of the industry are being conducted to enhance exhibition performance as in the United States or Europe. Some studies are focusing particularly on analyzing visiting patterns of exhibition visitors using intelligent information technology in consideration of the variations in effects of watching exhibitions according to the exhibitory environment or technique, thereby understanding visitors and, furthermore, drawing the correlations between exhibiting businesses and improving exhibition performance. However, previous studies related to booth recommendation systems only discussed the accuracy of recommendation in the aspect of a system rather than determining changes in visitors' behavior or perception by recommendation. A booth recommendation system enables visitors to visit unplanned exhibition booths by recommending visitors suitable ones based on information about visitors' visits. Meanwhile, some visitors may be satisfied with their unplanned visits, while others may consider the recommending process to be cumbersome or obstructive to their free observation. In the latter case, the exhibition is likely to produce worse results compared to when visitors are allowed to freely observe the exhibition. Thus, in order to apply a booth recommendation system to exhibition halls, the factors affecting the performance of the system should be generally examined, and the effects of the system on visitors' unplanned visiting behavior should be carefully studied. As such, this study aims to determine the factors that affect the performance of a booth recommendation system by reviewing theories and literature and to examine the effects of visitors' perceived performance of the system on their satisfaction of unplanned behavior and intention to reuse the system. Toward this end, the unplanned behavior theory was adopted as the theoretical framework. Unplanned behavior can be defined as "behavior that is done by consumers without any prearranged plan". Thus far, consumers' unplanned behavior has been studied in various fields. The field of marketing, in particular, has focused on unplanned purchasing among various types of unplanned behavior, which has been often confused with impulsive purchasing. Nevertheless, the two are different from each other; while impulsive purchasing means strong, continuous urges to purchase things, unplanned purchasing is behavior with purchasing decisions that are made inside a store, not before going into one. In other words, all impulsive purchases are unplanned, but not all unplanned purchases are impulsive. Then why do consumers engage in unplanned behavior? Regarding this question, many scholars have made many suggestions, but there has been a consensus that it is because consumers have enough flexibility to change their plans in the middle instead of developing plans thoroughly. In other words, if unplanned behavior costs much, it will be difficult for consumers to change their prearranged plans. In the case of the exhibition hall examined in this study, visitors learn the programs of the hall and plan which booth to visit in advance. This is because it is practically impossible for visitors to visit all of the various booths that an exhibition operates due to their limited time. Therefore, if the booth recommendation system proposed in this study recommends visitors booths that they may like, they can change their plans and visit the recommended booths. Such visiting behavior can be regarded similarly to consumers' visit to a store or tourists' unplanned behavior in a tourist spot and can be understand in the same context as the recent increase in tourism consumers' unplanned behavior influenced by information devices. Thus, the following research model was established. This research model uses visitors' perceived performance of a booth recommendation system as the parameter, and the factors affecting the performance include trust in the system, exhibition visitors' knowledge levels, expected personalization of the system, and the system's threat to freedom. In addition, the causal relation between visitors' satisfaction of their perceived performance of the system and unplanned behavior and their intention to reuse the system was determined. While doing so, trust in the booth recommendation system consisted of 2nd order factors such as competence, benevolence, and integrity, while the other factors consisted of 1st order factors. In order to verify this model, a booth recommendation system was developed to be tested in 2011 DMC Culture Open, and 101 visitors were empirically studied and analyzed. The results are as follows. First, visitors' trust was the most important factor in the booth recommendation system, and the visitors who used the system perceived its performance as a success based on their trust. Second, visitors' knowledge levels also had significant effects on the performance of the system, which indicates that the performance of a recommendation system requires an advance understanding. In other words, visitors with higher levels of understanding of the exhibition hall learned better the usefulness of the booth recommendation system. Third, expected personalization did not have significant effects, which is a different result from previous studies' results. This is presumably because the booth recommendation system used in this study did not provide enough personalized services. Fourth, the recommendation information provided by the booth recommendation system was not considered to threaten or restrict one's freedom, which means it is valuable in terms of usefulness. Lastly, high performance of the booth recommendation system led to visitors' high satisfaction levels of unplanned behavior and intention to reuse the system. To sum up, in order to analyze the effects of a booth recommendation system on visitors' unplanned visits to a booth, empirical data were examined based on the unplanned behavior theory and, accordingly, useful suggestions for the establishment and design of future booth recommendation systems were made. In the future, further examination should be conducted through elaborate survey questions and survey objects.