This study deals with grasping the characteristics of human emotion and linking with design elements of specific shopping mall website. In order to develop the emotional shopping mall site environment, it extracts shopping malls that are commonly used by users and designs emotional spaces by analyzing emotional design elements about the environment of shopping mall sites. As a result of this study, it is possible to group the internet shopping sites by analyzing the emotional design of the internet shopping mall site and the similarities of the features of each Internet. It can be designed as a link between an internet site with similar characteristics and emotional vocabulary. Based on the results of this study, it is meaningful to suggest a design method to search for directions that are more efficient and stimulate the senses in the internet shopping through grouping by individual characteristics and similarity of shopping mall internet site.

Recently, product-service integration has been discussed as an important driver for technological innovation. However, limited attention has been paid to investigate and identify emerging technologies that are expected to be effectively converged for innovation. Even some previous works have discussed product-service convergence using patent analysis, they employed link prediction based on similarity measures. Therefore, this study aims to suggest a patent-based framework that can be used for investigating and identifying promising technologies for product-service convergence. First, this study defines service technology and classifies current patent classification into manufacturing IPCs and service IPCs. Then, we analyzed the convergence between manufacturing IPCs and service IPCs using network analysis. Next, we suggested five patent-based indicators to identify promising technologies - convergence strength, convergence speed, convergence flexibility, convergence novelty, and convergence brokerage - and identified promising technologies. This study is expected to be used for analyzing and identifying promising technologies under circumstances where technology convergence plays a key role in innovation.

This study aims to investigate the relationship between entrepreneurship, organizational grit, and management performance in a rapidly changing business environment with trade disputes and the Fourth Industrial Revolution. The study was conducted in the form of a questionnaire and was based on data collected by 445 workers of Korean SMEs. The results show that proactiveness and risk-taking of entrepreneurship positively impact the consistency of interests in organizational grit, and innovativeness and proactiveness of entrepreneurship positively impact the perseverance of effort in organizational grit. proactiveness has a positive impact on both the financial and non-financial performance of management performance. In addition, the perseverance of effort in organizational grit has been proven to have a positive impact on the financial performance of management performance.

The purpose of this study was to identify the innovation capabilities of SMEs manufacturing firms promoting smart factories to secure or strengthen their internal and external competitiveness. As core innovation capability, R&D capability, production capability, learning capability and marketing capability were considered by based on the previous studies, and all five sub-factors were selected. Smart meisters are those who are dispatched to SMEs manufacturing firms to support the work required to build smart factories. The data that evaluated the innovation capability of the firms in charge of smart meisters importance and performance were analyzed by applying the revised IPA. The research results are as follows. First, the capacity to be secured in order to strengthen the competitiveness of SMEs was production capability and learning capability. More specifically, the effective operation of the production system(B3), the appropriateness of quality management activities (B4) which are sub-factor of production capability(B), the sharing of information and knowledge(C2) and the provision of learning opportunities for knowledge acquisition(C5) which are sub-elements of learning capability(C), identified the need for intensive investment.

As AI(artificial intelligence) is actively researched, it is being applied in various fields such as natural language processing, video and voice processing. However, voices pointing out the technical limitations of deep learning are spreading, and accordingly, researches for solving the technical limitations of deep learning are being actively conducted. In this paper, BERT, well known as the pre-training model of natural language processing, was applied to the classification problem of legal counseling data to verify the effect of transfer learning. Using BERT pre-trained data, the Transformer classification model was implemented and applied to the problem of legal counseling data classification, which showed higher accuracy than the traditional machine learning algorithm.

Most of the research on the vehicle route problem is about improved neighboring search method because it can save the time required to repeat the search process by efficiently constructing good neighbors. However, when comparing and evaluating the results of the proposed algorithm, there is a limit to evaluating it based on one meta heuristic. Therefore, in this paper, rather than presenting a new algorithm for the vehicle route problem, GLS, TSA, SA and greedy descent algorithm(GDA), which are representative meta-heuristics widely used to solve various types of vehicle route problems, are applied to CVRP problems and compared and analyzed. Through this, we tried to compare and evaluate the characteristics of four representative meta-heuristic techniques. For this purpose, the comparison and analysis between the techniques were applied to the CVRP benchmark problems known to be optimal. Even when the number of vehicles is large or at least the service capacity of the vehicle is variable and the number of demands increases, the guided local search (GLS) provides the best route in most situations. Another interesting thing about the experiments in this paper is that SA's solutions present the same results as the results of GDA in every model tested.

The purpose of this study is to examine the effects of the intentions to accept new technology of consumers who have experience in carrying out orders and payments using the smart order system(SOS), which has been recently spread mainly in the coffee franchise industry, on their behavior of use in order to present ways for effective use of the smart order system(SOS). To this end, attempts were made to identify the relationships between performance expectancy (PE), effort expectancy (EE), social impact(SI), and personal innovativeness (PI) and the behavior of use(BU), which are variables used in the Unified Theory of Acceptance and Use of Technology(UTAUT) among innovative technology acceptance models and whether differences between males and females have moderating effects was tested using gender (G), which is the sexes of males and females, as a moderating variable. The analyzed results of this study are summarized as follows.
First, Performance Expectancy(PE) has significant positive(+) effects on smart order system users' behavior of use. Second, Social Impact(SI) has significant positive(+) effects on smart order system users' behavior of use. On the other hand, Effort Expectancy(EE) has no significant positive(+) effect on smart order system users' behavior of use. Fourth, Personal Innovativeness(PI) was shown to have no significant positive(+) effects on smart order system users' behavior of use. Finally, differences between the Genders(G) of males and females were found to have no moderating effect on smart order system users' behavior of use.

While there has been a strong emphasis on voluntary collaboration and partnership among participants in the supply chain, the relationship among companies with different power and influence has not been studied well. Supply chain partnership implies that the participants in the supply chain are equally important and their relationship is horizontal. However, in vertically integrated B2B (Business-to-Business) supply chains, customers tend to have more power and bigger in size and they may be leading the relationships with suppliers with less power and smaller scale. Supply chain leadership implies that the participants with more power are leading and coordinating the whole supply chain to maximize the supply chain wide benefits. Customers with supply chain leadership may consider not only their interests but also partners' interests. Accordingly, this study analyzed the relationship between supply chain leadership and partnership in terms of supply chain performance based on a structural equation model. The structural equation model has been analyzed with PLS (Partial Least Square) methodology. The results confirm that supply chain leadership factors contribute to supply chain performance through emotional supply chain partnership attributes. We found that the leadership perspectives such as long-term trust and commitment are more important than the contractual partnerships.

Although Additive Ratio Assessment(ARAS) is a convenient and practical technique for use in muti-criteria decision making method(MCDM), there has been only research on the benefit and non-beneficial criteria.
This study proposes a target based normalization formular for ARAS. To verify the proposed values, I present the normalization values of the model with nominal-is-best and the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) with larger-the-better.
I also provide a revised ARAS model that combines the normalized value and reference sequence of Grey Relational Analysis(GRA) and the weight obtained using Analytic Hierarchy Process(AHP).
To compare the results of this study, this paper uses the location selection problem for distribution centers cases presented, and shows Spearman's rank correlation coefficient to identify the rank similarity between the considered methods.