• Fashion & Textile Research Journal
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• v.25 no.3
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• pp.280-290
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• 2023

As consumers are increasingly shopping online for fashion products, their return behavior is also increasing. Regarding the factors affecting return behavior, this study explores the effect of the purchasing orientation considering returns that are derived from bracketing purchase behavior, monetary lenient return policies, and non-monetary lenient return policies. Additionally, this study examines the effect of monetary/non-monetary lenient return policies on return behavior, mediated by the purchasing orientation considering returns. This study was conducted through an online survey and 238 data were collected and used for analysis. Two research models were designed for each independent variable of monetary lenient return policies, and non-monetary lenient return policies, and the path of the research model was analyzed using Process Macro 4.0. The study found that the sub-dimensions of return policy - monetary or non-monetary return policies - had different effects on return behavior through purchasing orientation considering returns. Monetary lenient return policies had a positive direct effect on return behavior, and purchasing orientation considering returns mediated the effect of the monetary lenient return policies on return behavior. However, the non-monetary lenient return policies only positively and significantly directly affected return behavior. The findings of this study contribute to understanding consumers' purchasing orientation considering returns. Furthermore, from the effect of the return policy on return behavior, the results are valuable as they can help fashion marketers establish a return strategy.

• International Area Studies Review
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• v.13 no.1
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• pp.81-102
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• 2009

The discussion of the relationship between macro-economic variables is very important research topic. the most economic variables discussed in connection with the liberalization of capital is the exchange rate and stock prices and these two variables have a relationship of mutual influence are identified. However, the results on the time frequency and the time span of a variable appear differently. Therefore, the purpose of this research describes a cause that the result of prior research varied and presents more reliable research methodology. In this research, when the time frequency and span varied, the VAR analysis of the exchange rate and stock prices appeared differently. So, we use the Monte Carlo simulation method in order to performing our purpose. Our research supports the existing research said the ratio that each coefficient VAR model contained 95% confidence interval of estimated coefficient in Monte Carlo simulation is higher when it is applied more the long term and frequent observation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.167-184
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• 2020

This study analyzed the effects of information orientation and technology commercialization ability on technological performance of corporate workers. Information Orientation consisted of information technology capability, information management ability, information behavior and value, and technology commercialization capability consisted of productization capability, production capability, and marketing capability as sub-variables, and technology accumulation capacity was used as a coordinating variable. An empirical analysis was performed on 349 online and offline questionnaires collected from corporate employees. Analysis results using SPSS v22.0 and Process macro v3.4 First, information orientation and technical performance were found to have a significant effect.In addition, information orientation had a significant effect on technology commercialization capability. The magnitude of the influence on the productive capacity and the productive capacity in the variable of competency was in the order of information technology ability, information management ability, information behavior and value, but the influence on marketing capability was different from the previous results. Information management ability and information technology ability were in order. Second, the product commercialization capability, production capability, and marketing ability of technology commercialization ability had a significant effect on technology performance independently of information orientation. Third, the information technology ability and information management ability had a significant influence on the technical performance, but the indirect effect through the commercialization ability and marketing ability in information behavior and value was significant, the indirect effect of transit was not significant. Fourth, only the interaction terms of production capacity and technology accumulation capacity were significant among the sub-variables of technology commercialization capacity, and technology accumulation capacity, commercialization capacity, and marketing ability were not significant. Therefore, the relationship between productive capacity and technological performance can be interpreted as lower in firms with high technology accumulating ability than in lower firms, subsequent studies will require the introduction of other independent variables, models through the introduction of parameters and control variables.

• Land and Housing Review
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• v.4 no.1
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• pp.43-54
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• 2013

This This paper investigates the variation of the factors to determinate housing price in Seoul metropolitan area after sub-prime financial crisis, in Korea, using a VAR model. The model includes housing price and housing rent (Jeonse) in Seoul metropolitan area from 1999 to 2011, and uses interest rate, real GDP, KOSPI, Producer Price Index and practices to impulse response and variance decomposition analysis to grasp the dynamic relation between a variable of macro economy and and a variable of housing price. Data is classified to 2 groups before and after the 3rd quater of 2008, when sub-prime crisis occurred; one is from the 1st quater of 1999 to the 3rd quater of 2008, and the other is from the 2nd quater of 1999 and the 4th quater of 2011. As a result, comparing before and after sub-prime crisis, housing price is more influenced by its own variation or Jeonse price's variation instead of interest rate and KOSPI. Both before and after sub-prime financial crisis, Jeonse price is also influenced by its own variation and housing price. While after sub-prime financial crisis, influences of Producer Price Index, KOSPI and interest rate were weakened, influence of real GDP is expanded. As housing price and housing rent are more influenced by real economy factors such as GDP, its own variation than before sub-prime financial crisis, the recent trend that the house prices is declined is difficult to be converted, considering domestic economic recession and uncertainty, continued by Europe financial crisis. In the future to activate the housing business, it ia necessary to promote purchasing power rather than relaxation of financial and supply regulation.

• International Area Studies Review
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• v.22 no.3
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• pp.29-66
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• 2018

The purpose of the study was to point out the limitation of the conceptual discussions in which researches on gender responsive budgeting have remained so far and to empirically analyze the effect of institutionalization of gender responsive budgeting on the gender equality by using macro data. The units of the analysis were 73 countries which implements gender responsive budgeting among the 229 countries registered in the World Bank. Panel data were established on the materials of 7-year period from 2006 to 2012, which were analyzed by Fixed Effect Model. Gender Equality (Gender Gap Index) which is the ultimate goal of gender budgeting was established as the dependent variable while Institutionalization of Gender Responsive Budgeting (formal and qualitative classification) was established as the independent variable. In addition, social and economic factors, political factors and geographical factors which were judged to affect dependent variables were established as control variables. As a result of analysis, the institutionalization of gender responsive budgeting has positive effect on gender equality. Thus, the study confirmed that gender responsive budgeting has positive effect on gender equality in countries with legal, procedural and formal foundations rather than in countries with simple rhetoric in catchwords and documents. Moreover, the higher the level of institutionalization of gender responsive budgeting is, the more positive effect it has on the gender equality. Therefore, the study found out that efforts need to be accompanied to enhance the level of institutionalization in order to increase the effectiveness of institutionalization of gender responsive budgeting.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.225-239
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• 2022

This study investigated the effect of digital agriculturalization factors on business performance with the use of financial support as a moderating variable for agricultural firm workers. The factors of digital agriculture were divided into digital technology innovation orientation, administration innovation orientation, healthiness of ecosystem and entrepreneurship orientation, and business performance was set as a dependent variable. 212 questionnaires collected from workers in agricultural businesses located across the country were used for empirical analysis. Analysis results using SPSS v22.0 and Process macro v3.4 are as follows: First, digital technology innovation orientation, administration innovation orientation, and entrepreneurship orientation have a significant effect on business performance, and the effect of ecosystem health on business performance is appeared to be insignificant. Second, the use of financial support was found to significantly moderating the relationship between digital technology innovation orientation and business performance, entrepreneurship orientation and business performance. On the other hand, it was found that the relationship between operational innovation orientation, business performance, and healthiness of ecosystem and business performance were not significantly moderated In addition, as a follow-up study, a study on the mediation model formed by the discovery of mediators and a study for a moderated mediation analysis through a conditional process model with additional mediators are required.

• Economic Analysis
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• v.27 no.4
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• pp.1-42
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• 2021

The outlook for Korea's consumer price inflation rate has a profound impact not only on the Bank of Korea's operation of the inflation target system but also on the overall economy, including the bond market and private consumption and investment. This study presents the prediction results of consumer price inflation in Korea for the next three years. To this end, first, model selection is performed based on the out-of-sample predictive power of autoregressive distributed lag (ADL) models, AR models, small-scale vector autoregressive (VAR) models, and large-scale VAR models. Since there are many potential predictors of inflation, a Bayesian variable selection technique was introduced for 12 macro variables, and a precise tuning process was performed to improve predictive power. In the case of the VAR model, the Minnesota prior distribution was applied to solve the dimensional curse problem. Looking at the results of long-term and short-term out-of-sample predictions for the last five years, the ADL model was generally superior to other competing models in both point and distribution prediction. As a result of forecasting through the combination of predictions from the above models, the inflation rate is expected to maintain the current level of around 2% until the second half of 2022, and is expected to drop to around 1% from the first half of 2023.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.2
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• pp.195-205
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• 2012

This study examines runaway youths at risk in a youths' shelter who are preparing for an independent life and both the facilitating and adverse factors to personal characteristics and independence of runaway youths at risk with the aim to grasp their recognition of independence and level of desire for it and find out necessary factors for a successful independence in multidimensional perspectives including the economic independence, educational independence, psychological independence, and social independence for their sound growth. This will provide the basis for desirable interventions for youths runaway youths at risk to prepare for an independent life. The findings of this study on the factors that affect the preparation for an independent life are as follows: First, as a result of analyzing the effect of micro-systematic factors on the preparation for an independent life, it turned out that problem-solving abilities and self-efficacy had influence on the preparation for a career Second, as a result of analyzing the effect of mesoscopic-systematic variables on the preparation for an independent life, it turned out that the preparation for a career were affected by whether to participate in independence preparation programs and institutional supports, and that career maturity of runaway youths at risk were affected only by the relationship with teachers and participation in independence preparation programs. Third, as a result of analyzing the effect of macro systematic variables on the preparation for an independent life, it turned out that the preparation for a career were affected by participation of the local community and service network, and that participation of the local community was an predictor variable that would affect a career maturity of runaway youths at risk. Fourth, as a result of analyzing ecological systematic variables that might affect the preparation for a career, it turned out that intervening variables and macro systematic variables had the most powerful influence on the preparation for a career among runaway youths at risk. It is necessary, therefore, to provide education programs organized by policies in order to develop problem-solving abilities and vocational capabilities so that runaway youths at risk, and to train and appoint more professional teachers at shelters. Programs for independence preparation need to be developed actively and practically in consideration of the characteristics of shelters, and the network with the local community for support also need to be established in utilization of the human resources and service programs of the community. With the understanding of leaving home of runaway youths at risk as the previous stage of an independence, there should be a housing support for their stable settlement in the perspective of housing welfare until become adults. In addition, there should be education specialized programs for occupation and careers to train runaway youths at risk as professionals including such areas as health, mentality, learning, and voluntary work for their sound growth.