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The purpose of this paper is to propose a quantitative method for identifying multiple and hierarchical knowledge trajectories within a specific technological domain (TD).

The proposed method as a patent-based data-driven approach is basically based on patent classification systems and patent citation information. Specifically, the method first analyzes hierarchical structure under a specific TD based on patent co-classification and hierarchical relationships between patent classifications. Then, main paths for each sub-TD and overall-TD are generated by knowledge persistence-based main path approach. The all generated main paths at different level are integrated into the hierarchical main paths.

This paper conducted an empirical analysis by using Genome sequencing technology. The results show that the proposed method automatically identifies three sub-TDs, which are major functionalities in the TD, and generates the hierarchical main paths. The generated main paths show knowledge flows across different sub-TDs and the changing trends in dominant sub-TD over time.

To the best of the authors’ knowledge, the proposed method is the first attempt to automatically generate multiple hierarchical main paths using patent data. The generated main paths objectively show not only knowledge trajectories for each sub-TD but also interactive knowledge flows among sub-TDs. Therefore, the method is definitely helpful to reduce manual work for TD decomposition and useful to understand major trajectories for TD.

The purpose of this paper is to propose a high‐mobility in‐pipe robot platform and its navigation strategy for navigating in T‐branch pipes efficiently.

For high mobility, this robot is developed based on inchworm locomotion. An extensor mechanism with flexible links and clamper mechanisms enable the robot to conduct both steering and inchworm locomotion. The locomotion of the robot is modeled based on a pseudo‐rigid‐body model. From the developed model, this paper introduces a navigation strategy based on defining relay points and generating a path from a main pipe to a T‐branch pipe.

With this navigation strategy, the robot can avoid collisions and enter T‐branch pipes effectively. The path generation algorithm is verified by experiment. In addition, both the navigation strategy and mobility of the robot are demonstrated by experiments conducted in a commercial pipe configuration.

This paper describes the mechanism of an inchworm‐type in‐pipe robot that is able to steer and adapt to pipe diameter changes. This paper also describes navigation strategy that enables a robot to avoid collisions and enter T‐branch pipes effectively. This research will help the construction of a fully autonomous in‐pipe robot that can navigate through various types of pipes.

The purpose of this paper is to test the dual frames of reference theory. For the test, the reference point hypothesis examines whether the difference in the quality of social conditions between the home and host countries determines the variations of immigrants’ trust in the institutions of their host country.

By using hierarchical linear modeling analysis, the current study examines whether “difference of homicide rate from South Korea” or “difference of level of democracy from South Korea” influences immigrants’ confidence in the police. Using data collected from nine different immigrant groups in South Korea, the current study examined both country-level factors as well as individual-level factors.

According to the analysis results, the difference of level of democracy from South Korea significantly influenced immigrants’ confidence in the South Korean police. Specifically, when immigrants came from democratically under-developed countries, they showed a relatively high level of confidence in the South Korean police.

Confidence in the police among the first generation of immigrants has recently attracted increasing attention. However, no previous studies have examined immigrants’ confidence in the police within an Asian country. Thus, the current study might contribute to generating better police performances toward first-generation immigrants who tend to be discriminated against and are also vulnerable to various forms of victimization because of their new status in a new society.

The purpose of this paper is to explore the relationship between social capital and collective action at the county level in the US while incorporating the moderating effects of community racial diversity and urbanity and to find the changing effects of social capital on philanthropic collective action for community education.

This paper employs a quantitative research design. The dependent variable measures philanthropic collective action for community education while the independent variable for social capital is measured as a community level index. Moderating variables include a community racial diversity index and urbanity. This analysis tests and interprets interaction effects using moderated multiple regression (MMR), with the baselines of MMR being grounded to multivariate ordinary least squares (OLS) regression. Analyses are carried out in the context of the USA during 2006 and 2010, with US counties employed as the unit of analysis.

The effects of social capital on philanthropic contributions decline in counties with low- and mid-levels of racial diversity. On the contrary, the effects of social capital increase in highly racially diverse counties. The three-way interaction model result suggests that racial diversity positively moderates social capital on philanthropic collective action for community education where the effect of social capital is strong and positive in highly racially diverse urban communities.

This research complicates the notion that social capital and racial diversity are negatively associated when exploring collective action and community education, and suggests effects of social capital varies with moderating effects on philanthropic collective action for community education.

This study aimed to identify subgroups of esports players based on their gaming behavior patterns across game genres and compare self-efficacy, social efficacy, loneliness and three dimensions of quality of life between these subgroups.

324 participants were recruited from prolific academic to complete an online survey. We employed latent profile analysis (LPA) to identify subgroups of esports players based on their behavioral patterns across genres. Additionally, a one-way multivariate analysis of covariance (MANCOVA) was conducted to test the association between cluster memberships and development and well-being outcomes, controlling for age and gender as covariates.

LPA analysis identified five clusters (two single-genre gamer groups, two multigenre gamer groups and one all-genre gamer group). Univariate analyses indicated the significant effect of the clusters on social efficacy, psychological health and social health. Pairwise comparisons highlighted the salience of the physical enactment-plus-sport simulation genre group in these outcomes.

This study contributes to the understanding of the development and well-being benefits experienced by various esports consumers, as well as the role of specific gameplay in facilitating targeted outcomes among these consumer groups.

This study aimed to understand better what makes esports fans engage with streamers' live-streaming of esports gameplay. This study used the Theory of Planned Behavior (TPB) and additionally adopted streamer identification and esports game identification as moderating variables.

Data were collected from streamers' esports content streaming viewers over 18 years of age using an online survey in Amazon M-Turk (N = 307). Based on past esports live-streaming weekly watching hours, which range from 1 to 45 h, the participants were divided into lower (n = 152) and higher (n = 155) frequency groups. PLS-SEM and bootstrapping techniques were used to test the moderated mediation relationships among the constructs.

This study found a negative moderating effect of past watching experience on the relationship between attitudes and behavioral intention, and it positively moderated the path between perceived behavioral control and behavioral intention. Also, it was found statistically significant direct impacts of streamer identification (STI) and esports game identification (EGI) on attitude and subjective norms. While the indirect impact of STI on behavioral intention through attitude was statistically significant, there were no significant indirect impacts of EGI on attitude and behavioral intention through subjective norms.

Theoretically, this study extends the TPB model by exploring the two identifications (i.e. streamers and esports games) as antecedents of the focal TPB factors (i.e. attitudes, subjective norms and perceived behavioral control) and the moderating effect of prior experience based on high/low weekly watching frequencies. Practically, content creators of esports live-streaming and live-streaming platform managers can use the study’s findings to develop strategies to nurture their current and future viewership.

This paper investigates a retrospective on the Journal of Derivatives and Quantitative Studies (JDQS) on its 30th anniversary based on bibliometric. JDQSs yearly publications, citations, impact factors, and centrality indices grew up in early 2010s, and diminished in 2020. Keyword network analysis reveals the JDQS's main keywords including behavioral finance, implied volatility, information asymmetry, price discovery, KOSPI200 futures, volatility, and KOSPI200 options. Citations of JDQS articles are mainly driven by article age, demeaned age squared, conference, nonacademic authors and language. In comparison between number of views and downloads for JDQS articles, we find that recent changes in publisher and editorial and publishing policies have increased visibility of JDQS.