A force-free field (FFF) is determined solely by the normal components of magnetic field and current density on the entire boundary of the domain. Methods employing three components of magnetic field suffer from overspecification of boundary conditions and/or a nonzero divergence-B problem. A vector potential formulation eliminates the latter issue, but introduces difficulties in imposing the normal component of current density at the boundary. This paper proposes four different boundary treatment methods within the vector potential formulation. We conduct a comparative analysis of the vector potential FFF solvers that we have developed incorporating these methods against other FFF codes in different magnetic field representations. Although the vector potential solvers with the new boundary treatments do not outperform our poloidal-toroidal formulation code, they demonstrate comparable or superior performance compared to the optimization code in SolarSoftWare. The methods developed here are expected to be readily applied not only to force-free field computations but also to time-dependent data-driven simulations.

Korean historical literatures offer numerous records on astronomical phenomena such as eclipses, comets, and close approaches, etc. Records of close approaches often use specific terms to describe the angular distance, which lack translation into modern numerical values. We study the usage of the five commonly used terms, namely, Entry (入, En), Invasion (犯, In), Occultation (掩, Oc), Eclipse (食, Ec), as well as the unit Chi (尺). Our analysis is based on more than 2,300 records from Goryeo (918–1392 CE) and Joseon (1392–1910 CE) Dynasties. Through statistical analysis, we determine their quantitative definitions. We convert the lunisolar calendar to the Julian and Gregorian date and utilize the modern ephemeris DE431 to calculate the angular distance between celestial bodies. We find that the angular distances of the terms En, In, Oc, and Ec correspond to respectively 1.78◦+2.36 −1.11, 0.89◦+3.54 −0.51, 0.44◦+1.15 −0.31, and 0.29◦+2.61 −0.16 for the Goryeo Dynasty and 1.36◦+1.15 −0.64, 0.51◦+1.11 −0.32, 0.25◦+0.27 −0.17, and 0.21◦+0.25 −0.11 for the Joseon Dynasty. Additionally, we determine the angular size of the unit Chi by using the records from Korean chronicles along with the drawings of comets’ tails in the Daily Log (天變謄錄). We estimate the unit Chi to be 1.11◦+0.46 −0.40 and find that the numerical definition was consistent throughout the two dynasties in Korea. Furthermore, we find that the terms were used to describe the closest approach and that there is no observational bias in the angular distances against the apparent magnitudes of the objects. We show that the terms En, In, Oc, and Ec represent decreasing angular distance in that order and this ordering was consistent in both dynasties.

인공 고관절 치환술에 사용되는 금속 삽입물은 크기와 성분에 따라 주변 조직과 크고 작은 자화율의 차이를 일으켜 다양한 금속 인공물의 원인이 되며, 영상에 진단적 가치를 떨어뜨린다. 수신대역폭을 높이는 것은 인공물 감소에 효과가 있으나, 높은 수신대역폭은 획득 영상의 신호대잡음비를 감소시키는 단점이 있어 일정 수치 이상으로는 적용 하기에는 어려움이 있다. 딥러닝 알고리즘은 영상의 신호대잡음비를 높이고 전체 영상에서 균일하게 배경 잡음을 제거하는 데 매우 효과적이다. 이에 본 연구에서는 금속 인공물 감소를 위해 기존에 높은 수신대역폭을 이용하는 MARS(metal artifact reduction sequence) 프로토콜과 더욱 높은 수신대역폭을 설정한 프로토콜(Ultra MARS) 을 획득한 후 딥러닝을 이용하여 딥러닝 Ultra MARS로 변환한 후에 금속 인공물의 차이를 비교하였다. 딥러닝 적 용 후 Ultra MARS에서 적용 전 또는 기존의 MARS 기법보다 인공물의 크기가 작게 측정이 되었다. 또한, 인공물의 전체적인 SSIM(structural similarity index measure)에서도 기존의 MARS 기법보다 전체면적이 작게 측정되었 다. 더 나아가 SSIM의 결과 딥러닝 적용 전후의 구조적 유사성 역시 유사하게 나왔다. 딥러닝 알고리즘을 기존에 인공물을 줄이기 위해 사용하는 MARS와 같은 기법에서도 월등하게 높은 수치를 사용하는 강조영상을 획득 가능하 며 영상의 인공물도 줄이며, 영상의 대조도 또한 유지되는 영상을 제공할 수 있을 것으로 사료된다.

This study aimed to explore the role of inference making in the relation between vocabulary knowledge (breadth and depth) and reading comprehension for 487 ninthgrade Chinese EFL students who were categorized as either struggling or adequate. Path analysis was used to examine both direct and mediated effects. The results indicated a statistically significant indirect effect of vocabulary knowledge on reading comprehension, mediated by inference making, for the entire participant group. However, there were notable differences between the struggling and adequate readers, as evidenced by distinct path diagrams. For struggling readers, the indirect effect of vocabulary breadth on reading comprehension through inference making was significant, while that of vocabulary depth was not significant. For adequate readers, both vocabulary breadth and depth directly explained reading comprehension. These results are discussed in the EFL context, encompassing assessment and instructional implications for EFL readers with varying levels of reading abilities.

The RCEP is the largest FTA in the world. It was negotiated at a moment in history when criticism concerning globalization, multilateralism, and FTAs as effective tools for growth and well-being abounded. Those concerns have been aggravated by COVID-19 and the war in Ukraine, which affected not only world health but also increased protectionist temptations and disruptions in GVCs. This paper aims to analyze the likely contribution of this mega-deal, its economic and political variables, including the leadership that China will exert, and the objectives pursued during the negotiation. The agreement is contrasted with other major FTA, namely the CPTPP, the FTAAP and the Pacific Alliance, mainly in relation to integration efforts. It is concluded that the RCEP will indeed increase intraregional trade, although its full impact will take years to be felt. To maximize its impact, the RCEP needs to incorporate key current issues and new members to the pact.

본 연구는 혁신 생태계 조성을 통한 경제성장 뿐만 아니라 자기고용을 통한 실업해소, 성장 단계별 적절한 인재 채용을 통한 고용창출 등 작금에 우리가 직 면한 사회·경제적 문제를 해결하기 위한 수단으로 창업이 매력적인 대안이 될 수 있음을 전제하였다. 나아가, 이와 같은 전제를 바탕으로 실질창업 활성화에서 중요한 것은 기회인식임을 제안하였고 기회인식에 영향을 미치는 변수들을 규명 하였다. 구체적으로, 기업가정신이 기회발견행동 및 창업기회인식에 미치는 영향 과 기회발견행동이 창업기회인식에 미치는 영향을 구조방정식 모델을 통해 실증 하였다. 또한 기업가정신과 창업기회인식의 관계에서 기회발견행동의 매개효과를 실증하였다. 연구결과 첫째, 기업가정신은 창업기회인식은 물론 기회발견행동을 구성하는 4개의 하위변수에 모두 통계적으로 매우 유의미한 영향을 미치는 것으 로 나타났다. 둘째, 기회발견행동의 하위 변수 중 관찰과 아이디어 네트워킹은 창업기회인식에 통계적으로 유의미한 영향을 미치는 것으로 나타났다. 셋째, 기 업가정신이 창업기회인식에 미치는 영향에서 아이디어 네트워킹의 매개효과가 검증되었다. 본 연구는 이상의 실증분석 결과를 바탕으로 기업가정신 및 창업교 육 혁신을 중심으로 이론적·실무적 시사점을 제안하였음에 의의가 있다.

Previous studies offered inconsistent empirical results for the influence of customer participation on service satisfaction. One possible explanation for this inconsistency is that existing conceptualizations of customer participation do not clearly differentiate the distinct roles of customer participation in service. To address this gap, Dong and Sivakumar (2015) have proposed an updated classification for customer participation based on “output specificity,” which refers to the degree to that the nature of the output is influenced by the person who provides the resource. The output of the customer participation can either be “specific” or “generic”. The “specific output” is defined as the expected service outcome can be idiosyncratic depending on whether the service is provided by the customer or the employee. In contrast, “generic output” refers to expected service outcome is well defined regardless of whether it is delivered by the service provider or the customer. How output specificity of customer participation influences service satisfaction still lacks of empirical examination.

This study investigated how immersive VR store experience generated consumers’ urge to buy via self-imagery and pleasure. It also identified that the processing varied by the level of self-relevance to the VR store. The findings suggest that the impact of VR store experience can be expanded to impulsive/compulsive purchases.

Innovative payment methods, such as Bitcoin, may exhibit effects on consumer behavior besides known pain of paying effects. This study sheds light on spillover effects of innovative payment methods by giving evidence for an increase of consumers’ purchase intention caused by payment method innovativeness and mediated by perceived store innovativeness.

This abstract summarizes an early-stage research proposal examining the benefits of storytelling in marketing green brands. Many research studies have been published in the last decade observing the growth and popularity of sustainable products (e.g., Bhardwaj et al., 2020; de Souza Correa et al., 2022; Haider, Shannon, & Poschis, 2022; Lunde, 2018; Rajogopal, Mahajan, & Priya, 2021; Skackuskiene & Vilkaite-Vaitone, 2022; among many others). Only some of these products offered immediate economic benefits to consumers when introduced. Consumers were skeptical of the sustainability of the products (e.g., Matthes & Wonneberger, 2014), consumers felt the prices were higher than unsustainable products (e.g., Juan, Hsu, & Xie, 2017), and consumers felt that the company was greenwashing (e.g., Cho & Taylor, 2020). However, the story of these businesses imagining a green future was the main driving force in attracting and convincing consumers to switch regardless of the cost and risk involved in the decision (e.g., Moshood et al., 2022). Getting exposed to these exciting stories, consumers want to join and be part of them by purchasing green products. For example, when sustainable Toyota Prius and Tesla cars were first introduced, there were more economical and best-performing cars in the crowded US market (i.e., Toyota.com, 2023; Tesla.com, 2023). However, unlike conventional combustion engine cars, they had a story to tell. Then, and today, the companies sell the imaginary of a green and sustainable future for humankind. It is the same with the sustainable apparel brand, Patagonia, which has gained popularity throughout the years (Patagonia.com, 2023). Their products are expensive compared to their unsustainable competitors. However, consumers are willing to pay the price to be a part of the story that the brand narrates, promising a more sustainable future.

Digitalization and the emergence of online video platforms changed the way people communicate and made new marketing opportunities. As mobile short-form video has unique characteristics, more people tend to consume and produce diverse content in the digital environment. The purpose of this study aims to better understand the influence of short-form videos from a fashion marketing standpoint and delineate the driving factors through story types. Specifically, by adopting common traits of short-form video content and story types based on Greimas’ narrative theory, this study explores customers’ intention toward fashion purchases and electronic word of mouth. In this context, this paper contributes to activating short-form video content as a tool to promote fashion brands and products but also opening up the possibility to further study short-form videos.

In order to communicate brand concepts and values to the young generations, many brands are highly active on social media platforms such as Twitter, Facebook, and Instagram. Brand-Generated Content has already become the most common marketing strategy for fashion brands and plays a significant role in influencing consumers’ purchase intention. With increased competition on social media platforms, companies need to understand which posting features can bring in more consumer engagements such as number of likes and comments on social media platforms. In this paper, we develop (1) a model to predict the number of likes and (2) a methodology to detect anomaly of posts that have unusually high percentage of negative user comments based on Instagram design variables, including semantic text meanings, facial expressions, color scheme and background of photos, and post timing, among others. We collected a data set of brand-generated Instagram posts from ten fashion brands. The data covers the image, text, and user comments posted between 2019 and 2020. Image features were extracted using Convolutional Neural Network, and text topics were generated through Latent Dirichlet Allocation. Our results will help managers design Instagram posts to increase consumer engagement and to reduce negative consumer reactions.

Although the phenomenon of lead categories is well-documented in the marketing literature, our understanding of this important store choice factor remains limited. Lead categories are defined as those product categories that are so important for the shopping trip that they influence the consumer’s store choice decision. The purposes of this paper are to offer theoretical bases that explain why lead categories form and to understand how overall images of product quality, selection, and price affect lead category formation. The authors use theories of anchoring effects and automatic cognitive processing to offer theoretical explanations regarding why consumers form lead categories and how overall images of product quality, selection, and price affect lead category formation. Using survey data collected from consumers at two grocery stores, the authors find that positive overall product quality and selection images facilitate lead category formation and that an overall low-price image hinders it.

The original third places concept conveyed the offering of much-needed settings for social comfort, thereby complementing the absence of equal opportunities at home (1st place) or in the workplace (2nd place). 3rd place is a crucial term to connect customers’ social needs, perception of service encounters, and the service provider’s managerial operation. Following the Covid-19 outbreak, various distancing forces have impeded previously intense social interactions featuring human-human contact. The increased use of contactless services and social distancing measures has impacted these. Such measurements refer to mandatory actions to maintain a fixed physical distance from others (i.e., two meters or six feet) via seating arrangements or suggested signage. While such compliance practices successfully limited the spread of Covid-19, they were also a signal of regulated behaviors and acceptable personal boundaries. The current study addressed this question by conducting experiments in three scenarios: a café, restaurant, and sports stadium. Following Pine and Gilmore’s experience typology, the three represent a passive absorptive experience, an active absorptive experience, and an immersive experience.

Previous studies offered inconsistent empirical results for the influence of customer participation on service satisfaction. One possible explanation for this inconsistency is that existing conceptualizations of customer participation do not clearly differentiate the distinct roles of customer participation in service. To address this gap, Dong and Sivakumar (2015) have proposed an updated classification for customer participation based on “output specificity,” which refers to the degree to that the nature of the output is influenced by the person who provides the resource. The output of the customer participation can either be “specific” or “generic”. The “specific output” is defined as the expected service outcome can be idiosyncratic depending on whether the service is provided by the customer or the employee. In contrast, “generic output” refers to expected service outcome is well defined regardless of whether it is delivered by the service provider or the customer. How output specificity of customer participation influences service satisfaction still lacks of empirical examination.

The costs associated with law enforcement have seen a sharp increase, driven by rising personnel costs and the growing demand for policing services (Gascón, 2010; Urban Institute, 2020). Considerable discussion has arisen about how science can potentially help law enforcement “do more with less”, and some scholars have suggested introducing new crime control technologies to address this problem (e.g., Roach, 2022; Weisburd & Neyroud, 2011). With the onset of the COVID-19 pandemic, police departments around the world had additional demand, as they were made responsible for overseeing and ensuring compliance with COVID protocols. As a response, some countries (e.g., Singapore and China; Barrett, 2021) resorted to employing service robots either alongside or in place of police officers to assist with COVID-related compliance tasks.