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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.

After the Korean War, South Korean politics was dominated by national security concerns. Reversing Carl von Clausewitz's well-known dictum, in South Korea, “politics is the continuation of war by other means.” Until the late 1980s, politics in South Korea was far from democratic. South Korea had five direct presidential elections (1987, 1992, 1997, 2002, and 2007) and six national assembly elections (1988, 1992, 1996, 2000, 2004, and 2008) after the democratic transition of 1987. In 1992, a civilian candidate, Young Sam Kim, was elected president. Young Sam Kim (1993–1998) prosecuted and punished former generals turned presidents Doo Hwan Chun (1980–1988) and Tae Woo Roh (1988–1993) for corruption, mutiny and treason in 1995. Dae Jung Kim (1998–2003) was elected president in 1997. For the first time in South Korean political history, regime change occurred between a ruling party and an opposition party.

In this chapter, the change and continuity of civil–military relations through the fluctuating dynamics of the democratic transition and consolidation in South Korea is examined. A positive consolidation of democratic reform is one that, while securing indisputable civilian supremacy, grants the military enough institutional autonomy for the efficient pursuit of its mission. Civilian supremacy should be institutionalized not only by preventing military intervention in civilian politics but also by ensuring civilian control over the formation and implementation of national defense policy.

In sum, despite three terms of civilian presidency, civilian supremacy has not yet fully institutionalized. Although significant changes in civil-military relations did occur after the democratic transition, they were not initiated by elected leaders with the intention of establishing a firm institutional footing for civilian supremacy. South Korea's political leaders have not crafted durable regulations and institutions that will sustain civilian control over the military.

More than six decades, Korea is still divided. The most highly militarized zone in the world lies along the demilitarized zone. How to draw the line prudently between seeking national security and promoting democracy shall be the most delicate task facing all the civilian regimes to come in South Korea. That mission will remain challenging not only for civilian politicians but also for military leaders.

The purpose of this paper is to identify the cause how the student movement in South Korea enjoyed the golden age in the 1970–1990s and could not be revived since the late 1990s and cannot be played a pivotal role again.

This study adopts historical analysis as primary methodology, traced the historical evolution of South Korean student activism in the 1970–1990s through analyzing secondary Korean literature and newspaper on the particular struggle cases in the period.

Social solidarity between society and student had played a pivotal role in the South Korean students' long activism in the struggle of the 1970–1990s. In the 1970–1980s, democratic election and constitutional reform set in the main purpose of struggle that attracted wide support from society and enjoyed maintaining a new member supply and their commitment despite authoritarian government's persistent oppression. When the sixth constitution was passed in 1987 with Democratization, the student decided to choose continuing struggle and set social cooperation with North Korea as the new goal, the sensitive issue in South Korea that confronted fierce criticism. Society chose to withdraw their support to the activism in the Yonsei University incident of 1996, rung a knell of long struggle since the 1970s.

The research identified the cause how South Korean students in university could persist long strike without particular internal resource production during three decades and ended the long struggle in the late 1990s; the existence of social solidarity between student and society was the main reason of continued new member supply and their commitment in the battle.

The purpose of this paper is to propose an interactive 2D–3D garment parametric pattern-making and linkage editing scheme that integrates clothing design, simulation and interaction to design 3D garments and 2D patterns. The proposed scheme has the potential to satisfy the individual needs of fashion industry, such as precise fit evaluation of the garment, interactive style editing with ease allowance and constrained contour lines in fashion design.

The authors first construct a parametric pattern-making model for flat pattern design corresponding to the body dimensions. Then, the designing 2D patterns are stitched on a virtual 3D mannequin by performing a virtual try-on. If the customer is unsatisfied after the virtual try-on, the adjustable parameters (appearance parameters and fit parameters) can be adjusted using the 2D–3D linkage editing with hierarchical constrained contour lines, and the fit evaluation tool interactively provides the feedback.

The authors observed that the usability and efficiency of the existing garment pattern-making method simplifies the garment pattern-making process. The authors utilize an interactive garment parametric flat pattern-making model to generate an individualized garment flat pattern that effectively adjust and realize the local editing of the garment pattern-making. The 2D–3D linkage editing is then employed, which alters the size and shape of garment pattern for a precise human model fit of the 3D garment using hierarchical constrained contour lines. Various instances have validated the effectiveness of the proposed scheme, which can increase the reusability of the existing garment styles and improve the efficiency of fashion design.

First, the authors do not consider the garment pattern-making design of sophisticated styles. Second, the authors do not directly consider complex garment shapes such as wrinkles, folds, multi-layer models and fabric physical properties.

The authors propose a pattern adjustment scheme that uses the 3D virtual try-on technology to avoid repetitions of reality-based fit tests and garment sample making in the designing process of clothing products. The proposed scheme provides interactive selections of garment patterns and sizes and renders modification tools for 3D garment designing and 2D garment pattern-making. The authors present the 2D–3D interactive linkage editing scheme for a custom-fit garment pattern based on the hierarchical constraint contour lines. The spatial relationship among the human body, pattern pieces and 3D garment model is adequately expressed, and the final design result of the garment pattern is obtained by constraint solving. Meanwhile, the tightness tension of different parts of the 3D garment is analyzed, and the fit and comfort of the garment are quantitatively evaluated.

This study aims to examine if the participation of live-stream influencers (LSIs) affects tipping frequency on live streaming platforms, and further investigate the mediating and moderating mechanisms.

Quasi-experiment and difference-in-differences models are used for data analysis. Propensity score matching is used to address potential unobservable endogeneity.

Real-time live streaming data reveal that LSIs’ participation significantly improves tipping frequency in live streaming rooms. Also, more users are attracted to the live streaming rooms and more users become active in participation. Additionally, the positive impact of LSIs’ participation is enhanced in the live streaming rooms with a greater number of relationship links between users.

The findings clarify the new role of influencers and reveal the mechanisms on how LSIs benefit the platforms.

The findings offer novel insights into implementing influencer marketing to interactive social media platforms, by encouraging influencer participation, user relationship building and influencer network growth.

This study highlights the value of LSIs for interactive social media platforms in terms of organic growth, revenue generation and cost reduction.

In the cold supply chain (SC), effective risk management is regarded as an essential component to address the risky and uncertain SC environment in handling time- and temperature-sensitive products. However, existing multi-criteria decision-making (MCDM) approaches greatly rely on expert opinions for pairwise comparisons. Despite the fact that machine learning models can be customised to conduct pairwise comparisons, it is difficult for small and medium enterprises (SMEs) to intelligently measure the ratings between risk criteria without sufficiently large datasets. Therefore, this paper aims at developing an enterprise-wide solution to identify and assess cold chain risks.

A novel federated learning (FL)-enabled multi-criteria risk evaluation system (FMRES) is proposed, which integrates FL and the best–worst method (BWM) to measure firm-level cold chain risks under the suggested risk hierarchical structure. The factors of technologies and equipment, operations, external environment, and personnel and organisation are considered. Furthermore, a case analysis of an e-grocery SC in Australia is conducted to examine the feasibility of the proposed approach.

Throughout this study, it is found that embedding the FL mechanism into the MCDM process is effective in acquiring knowledge of pairwise comparisons from experts. A trusted federation in a cold chain network is therefore formulated to identify and assess cold SC risks in a systematic manner.

A novel hybridisation between horizontal FL and MCDM process is explored, which enhances the autonomy of the MCDM approaches to evaluate cold chain risks under the structured hierarchy.

This paper aims to develop a quality evaluation model for artificial intelligence (AI)-based products/services that is applicable to startups utilizing AI technology. Although AI-based service has risen dramatically and replaced many service offerings, in reality, startups are rarely to develop and evaluate AI services. The features of AI service are fundamentally different from the properties of existing services and have a great influence on the customer's service selection.

This paper reviews startups' development process, existing quality evaluation models and characteristics of services utilizing AI technology, and develops a quality evaluation model for AI-based services. A detailed analysis of a survey (application of the model) on customer satisfaction for AI speakers is provided.

This paper provides seven key features and 24 evaluation items for evaluating AI-based services.

This paper contributes to the growing need for methodologies that reflect the new era of AI-based products/services in quality evaluation research.

The purpose of this study is to develop a decomposed model to inspect the effect of knowledge management practices (knowledge sharing culture [KSC], knowledge-based human resource management [KHRM], strategy and leadership [S&L], information and communication technology [ICT] on organizational performance [OP]) by using the four balanced scorecard outcomes (BSC) (learning and growth [L&G], internal process [IP] perspective, customer satisfaction [CS] perspective and financial performance [FP]).

The research methodology included development of a research model based on comprehensive literature review followed by survey of knowledge-intensive organizations. A sample of 277 employees was obtained and structured equation modeling analysis using SPSS AMOS was conducted to test the proposed hypotheses.

The study shows that KSC and KHRM have a highly significant effect on all the four aspects of OP; S&L positively and significantly affects only L&G and IP but does not have any significant effect on the other two, i.e. CS and FP, while ICT practices did not affect any of the measures significantly.

The data are limited to 277 middle and senior level managers of Indian firms, which may be a limiting factor for generalizability.

The proposed model uncovers the dynamics of individual relationships between KM practices and measures of performance (proposed by BSC) in comparison to existing models which have mainly focused on the overall effect.