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In an effort to reduce ambiguity around customs clearance of items deemed pernicious to public morality and present lessons for customs administration, this research aims to explore ways to improve customs clearance for RealDolls. Furthermore, by suggesting specific ideas to improve the process, this research also aims to contribute to the future customs clearance of socially controversial and legally ambiguous items.

The authors have decided to review studies from ethical and legal perspectives to focus on the legislation and its enforcement issues. The literature review is designed to provide insights on how to incorporate legal and ethical reasoning in the customs clearance process for RealDolls. Supplementary interviews were also conducted with criminal lawyers and customs officials to obtain expert knowledge on domestic legislation and customs control against the sex toys industry.

As a result of the study, it is found that a complete ban on RealDoll infringes on individuals' right to pursue happiness guaranteed by the Constitution and in most cases, cannot be implemented without loopholes. Therefore, it is suggested that the import regulation on RealDolls should be changed to the negative list system, which selectively disapproves certain RealDolls based on a list of RealDolls previously denied clearance by either the Supreme Court or the Customs Clearance Screening Committee. In addition, to have sufficient ethical and legal grounds, it is necessary to expand research on RealDolls regulation and actively introduce the process of obtaining social consensus.

There has been little discussion on regulating RealDolls on the customs clearance level; no specific criterion exists except the public morality clause. This study is vital in that it reviews issues of RealDolls customs clearance from legal and ethical perspectives. Doing so also has a practical significance of providing implications for the customs policies regarding items deemed pernicious to public morality.

In this paper, a three-dimensional (3D) printer-based manufacturing line and supporting system, which supports personalized/customized manufacturing for individual businesses or start-up companies, was studied to evaluate the practicality of using additive manufacturing for personalization/mass customization.

First, factory-as-a-service (FaaS) system, which provides factory as a service to customers, was proposed and designed to manufacture various products within a distributed manufacturing environment. This system includes 3D printer-based material extrusion processes, vapor machine/computer numerical control machines as post-processes and assembly and inspection processes with an automated material handling robot in the factory. Second, a virtualization module for the FaaS factory was developed using a simulation model interfaced with a cloud-based order and production-planning system and an internet-of-things-based control and monitoring system. This is part of the system for manufacturing operations, which is capable of dynamic scheduling in a distributed manufacturing environment. In addition, simulation-based virtual production was conducted to verify and evaluate the FaaS factory for the target production scenario. Main information of the simulation also has been identified and included in the virtualization module. Finally, the established system was applied in a sample production scenario to evaluate its practicality and efficiency.

Additive manufacturing is a reliable, feasible and applicable technology, and it can be a core element in smart manufacturing and the realization of personalization/mass customization.

Various studies on additive manufacturing have been conducted with regard to replacing the existing manufacturing methods or integrating with them, but these studies mostly focused on materials or types of additive manufacturing, with few advanced or applied studies on the establishment of a new manufacturing environment for personalization/mass customization.

This study aims to explore the relationships among antecedents (i.e. quality) and outcomes (i.e. trust, support, theme awareness and extension effect) of satisfaction at the 2013 Osong Cosmetics & Beauty (C&B) Expo held in Korea.

An onsite survey with self-administered questionnaires was administered for this study. A structural equation modeling (SEM) technique was used to analyze the relationships among ten constructs in the research model.

The results indicate that hospitality and product dimensions of quality positively affect satisfaction, satisfaction exerts positive influence on trust and theme awareness, trust performs an important role as a mediator between satisfaction and support and theme awareness significantly mediates satisfaction and extension effect.

This study encourages the Expo’s organizers to manage quality attributes to ensure Expo satisfaction and to consider extension effects of Expo experiences from long-term perspectives. This study also recommends that local governments develop symbolic products with exhibitors to strengthen the association of Expo themes with regions.

The current study highlights the role of quality as an antecedent of satisfaction with the C&B Expo, which has not been well-known despite its crucial role in the industry and the regional economy. It also improves the understanding of the inherent cause–effect relationships among antecedents and outcomes of Expo satisfaction. Therefore, this study provides crucial insights that the C&B Expo could be an effective means to reach target markets and stimulate trust from visitors, which, in turn, would encourage support for the C&B industry and extension effects for C&B products as a whole.

The Hanbo (meaning Korean treasure) scandal or “Hanbogate” occurred on January 23, 1997, with the bankruptcy of Hanbo Iron and Steel Company, the second largest steel company and 14th largest conglomerate in South Korea, as its debt had accumulated to US$5.6 billion. Hanbo's bankruptcy triggered an investigation by the Public Prosecutor's Office that resulted in the imprisonment for 15 years of Hanbo's founder, Chung Tae-Soo, for bribing politicians and bankers to pressure banks to extend hugh bank loans to Hanbo. Nine other persons were also convicted including Chung's son, who was jailed for three years for bribery and embezzlement, and Kim Hyun-Chol, the second son of President Kim Young-Sam, who was sentenced to three years jail and fined US$1.5 million (New York Times, 1997).

This study aims to develop a machine learning model to detect structure fire fatalities using a dataset comprising 11,341 cases from 2011 to 2019.

Exploratory data analysis (EDA) was conducted prior to modelling, in which ten machine learning models were experimented with.

The main fatal structure fire risk factors were fires originating from bedrooms, living areas and the cooking/dining areas. The highest fatality rate (20.69%) was reported for fires ignited due to bedding (23.43%), despite a low fire incident rate (3.50%). Using 21 structure fire features, Random Forest (RF) yielded the best detection performance with 86% accuracy, followed by Decision Tree (DT) with bagging (accuracy = 84.7%).

Limitations of the study are pertaining to data quality and grouping of categories in the data pre-processing stage, which could affect the performance of the models.

The study is the first of its kind to manipulate risk factors to detect fatal structure classification, particularly focussing on structure fire fatalities. Most of the previous studies examined the importance of fire risk factors and their relationship to the fire risk level.

The purpose of this paper is to analyze the relationship between new product diffusion and consumer internet search patterns using big data and to investigate whether such data can be used in forecasting new product diffusion.

This research proposes a new product diffusion model based on the Bass diffusion model by incorporating consumer internet search behavior. Actual data from search engine queries and new vehicle sales for each vehicle class and region are used to estimate the proposed model. Statistical analyses are used to interpret the estimated results, and the prediction performance of the proposed method is compared with other methods to validate the usefulness of data for internet search engine queries in forecasting new product diffusion.

The estimated coefficients of the proposed model provide a clear interpretation of the relationship between new product diffusion and internet search volume. In 83.62 percent of 218 cases, analyzing the internet search pattern data are significant to explain new product diffusion and that internet search volume helps to predict new product diffusion. Therefore, marketing that seeks to increase internet search volume could positively affect vehicle sales. In addition, the demand forecasting performance of the proposed diffusion model is superior to those of other models for both long-term and short-term predictions.

As search queries have only been available since 2004, comparisons with data from earlier years are not possible. The proposed model can be extended using other big data from additional sources.

This research directly demonstrates the relationship between new product diffusion and consumer internet search pattern and investigates whether internet search queries can be used to forecast new product diffusion by product type and region. Based on the estimated results, increasing internet search volume could positively affect vehicle sales across product types and regions. Because the proposed model had the best prediction power compared with the other considered models for all cases with large margins, it can be successfully utilized in forecasting demand for new products.

The purpose of this study is to examine the effect of background music on consumer's psychological and physiological responses when watching sports advertisements. We investigated how consumers' exposure to background music affects emotional arousal, attention, brand attitude and purchase intentions; and further tested consumers' information processing by using the same measures. Effects of music on viewer responses were hypothesized using arousal theory while the information processing was hypothesized using hierarchy-of-effects model.

We employed a between-subjects experimental design with random assignment. Fifty-four participants were recruited with 27 in an experimental group and 27 in a control group. Quantitative electroencephalogram (qEEG) and self-report measures were used to assess information processing. A multivariate analysis of covariance was conducted to compare the mean differences of variables between the groups. Partial least squares algorithm and bootstrapping were performed to further explore the relationships among the measures.

Mean differences indicated that the background music exposed group's emotional arousal, attention, brand attitude and purchase intention were significantly higher than those of the non-exposure group. Path analysis showed that the level of arousal induced by watching sports advertisements affected attention, attention affected brand attitude and brand attitude affected purchase intention. Indirect paths from arousal to brand attitude and attention to purchase intention were significant.

This study provides practical implications for sports marketers regarding methods to increase the effectiveness of sport advertisement. Results might contribute theoretically to the sports advertisement field by demonstrating the relationship between physiological and marketing-effect factors. Our method of measuring physiological response using qEEG is also expected to influence physiological measurement in sports marketing.

This paper, in face of the increasing interconnectivity between local and global, has attempted to retrospect the critical moment of Korean society under Tae‐woo Rho (1988–93) regime, in which Korea struggled for fundamental reforms of the earlier centrally controlled state system through economic rationalization and labor flexibilization. During that juncture of Korean history, neo‐liberalization under the influence of Fordian decline was a governing theme behind the Korean economy's policy formation as well as labor agenda. This reliance of government on the neo‐liberal pillar has made an impact on the subsequent leaderships under Young Sam Kim (1993–1998) and Dae Jung Kim (1998‐present). After briefly reviewing the major aspect of Korean economy and labor problems surrounding the financial crisis of East Asia around 1998, the international influence of Fordian decline and neo‐liberalization as a Korean alternative has been discussed.