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Recently, domestic market participants have a growing interest in synthetic Collateralized Debt Obligation (CDO) as a security to reduce credit risk and create new profit. Therefore, the valuation method and hedging strategy for synthetic CDO become an important issue. However, there is no won-denominated credit default swap transactions, which are essential for activating synthetic CDO transaction‘ In addition, there is no transparent market information for the default probability, asset correlation, and recovery rate, which are critical variables determining the price of synthetic CDO.

This study first investigates the method of estimating the default probability, asset correlation coefficient, and recovery rate. Next, using five synthetiC CDO pricing models‘ widely used OFGC (One-Factor Non-Gaussian Copula) model. OFNGC (One-Factor Non-Gaussian Copula) model such as OFDTC (One-Factor Double T-distribution Copula) model of Hull and White (2004) or NIGC (Normal Inverse Gaussian Copula) model of Kalemanova et al.(2005), SC<Stochastic Correlation) model of Burtschell et al.(2005), and FL (Forward Loss) model of Bennani (2005), I Investigate and compare three points: 1) appropriateness for portfolio loss distribution, 2) explanation for standardized tranche spread, 3) sensitivity for delta-neutral hedging strategy. To compare pricing models, parameter estimation for each model is preceded by using the term structure of iTraxx Europe index spread and the tranch spreads with different maturities and exercise prices Remarkable results of this study are as follows. First, the probability for loss interval determining mezzanine tranche spread is lower in all models except SC model than OFGC model. This result shows that all mαdels except SC model in some degree solve the implied correlation smile phenomenon, where the correlation coefficient of mezzanine tranche must be lower than other tranches when OFGC model is used. Second, in explaining standardized tranche spread, NIGC model is the best among various models with respect to relative error. When OFGC model is compared with OFDTC model, OFOTC model is better than OFGC model in explaining 5-year tranche spreads. But for 7-year or 10-year tranches, OFDTC model is better with respect to absolute error while OFGC model is better with respect to relative error. Third, the sensitivity sign of senior tranctle spread with respect to asset correlation is sometime negative in NIG model while it is positive in other models. This result implies that a long position may be taken by the issuers of synthet.ic COO as a correlation delta-neutral hedging strategy when OFGC model is used, while a short position may be taken when NIGC model is used.

This paper analyzes implied volatilities (IVs), which are computed from trading records of the KOSPI 200 index option market from January 2005 to December 2014, to examine major characteristics of the market pricing behavior. The data includes only daily closing prices of option transactions for which the daily trading volume is larger than 300 contracts. The IV is computed using the Black-Scholes option pricing model. The empirical findings are as follows;

Firstly, daily averages of IVs have shown very similar behavior to historical volatilities computed from 60-day returns of the KOSPI 200 index. The correlation coefficient of IV of the ATM call options to historical volatility is 0.8679 and that of the ATM put options is 0.8479.

Secondly, when moneyness, which is measured by the ratio of the strike price to the spot price, is very large or very small, IVs of call and put options decrease days to maturity gets longer. This is partial evidence of the jump risk inherent in the stochastic process of the spot price.

Thirdly, the moneyness pattern showed heavily skewed shapes of volatility smiles, which was more apparent during the global financial crises period from 2007 to 2009. Behavioral reasons can explain the volatility smiles. When the moneyness is very small, the deep OTM puts are priced relatively higher due to investors’ crash phobia and the deep ITM calls are valued higher due to investors’ overconfidence and confirmation biases. When the moneyness is very large, the deep OTM calls are priced higher due to investors’ hike expectation and the deep ITM puts are valued higher due to overconfidence and confirmation biases.

Fourthly, for almost all moneyness classes and for all sub-periods, the IVs of puts are larger than the IVs of calls. Also, the differences of IVs of deep OTM put ranges minus IVs of deep OTM calls, which is known to be a measure of crash phobia or hike expectation, shows consistent positive values for all sub-periods. The difference in the financial crisis period is much bigger than in other periods. This suggests that option traders had a stronger crash phobia in the financial crisis.

Many important constructs of business and social sciences are conceptualized as composites of common factors, i.e. as second-order constructs composed of reflectively measured first-order constructs. Current approaches to model this type of second-order construct provide inconsistent estimates and lack a model test that helps assess the existence and/or usefulness of a second-order construct. The purpose of this paper is to present a novel three-stage approach to model, estimate, and test second-order constructs composed of reflectively measured first-order constructs.

The authors compare the efficacy of the proposed three-stage approach with that of the dominant extant approaches, i.e. the repeated indicator approach, the two-stage approach, and the hybrid approach by means of simulated data whose underlying population model is known. Moreover, the authors apply the three-stage approach to a real research setting in business research.

The study based on simulated data illustrates that the three-stage approach is Fisher-consistent, whereas the dominant extant approaches are not. The study based on real data shows that the three-stage approach is meaningfully applicable in typical research settings of business research. Its results can differ substantially from those of the extant approaches.

Analysts aiming at modeling composites of common factors should apply the proposed procedure in order to test the existence and/or usefulness of a second-order construct and to obtain consistent estimates.

The three-stage approach is the only consistent approach for modeling, estimating, and testing composite second-order constructs made up of reflectively measured first-order constructs.

Though there is broad agreement on the beneficial impact of diversity in management and leadership roles, much of the innovative capacity of an organization is realized at the unit level in working teams. Recent research points to cultural diversity having an especially significant impact on innovation team performance. The reports also highlight the need for the optimal team operating principles to derive maximum benefit. To prepare such innovation teams for success, it is valuable to understand the dynamics of team diversity at the project level and the underlying barriers and opportunities presented.

This paper reviews the literature and case studies on cultural inputs to ideation and innovation, assessing team diversity through readily available instruments and the deployment of the science of team science (SciTS) principles in innovation teams.

The key learnings include the importance of establishing communication standards, SciTS principles, team assessment of thinking styles and the utility of cultural awareness instruments.

Diversity provides a creative advantage for innovation teams. However, team dynamics play an important role in maximizing these advantages, and cross-cultural competence of team members is required. Deployment of appropriate assessment tools and team methodologies enhances the likelihood of successful outcomes including in remote team settings.

Literature from diverse functional areas is summarized including the science of team science, organizational management, diversity and inclusion methodologies and ethnocultural dynamics. It provides pointers for the optimal formation and operating principles with highly culturally diverse teams.

In retrospectives on Brunei’s first feature film Gema Dari Menara (1968), commentators have tended to focus on either its historical representation of Brunei’s booming post-curfew years in the late 1960s as ‘a time capsule of Brunei’s lost pop history’, or the film’s propagandistic nature for Da’wah (religious propagation). In this paper, however, I will concentrate my observations on the aesthetic values of the film itself, including the narrative structure, plot design, camerawork, characterisation and character relationships, as well as the resulting artistic effects manifested by these production elements as a whole.

Putting all the propagandistic elements aside, I would like to argue that Gema Dari Menara, as a family melodrama, is carefully constructed and propelled by the above-mentioned filmmaking techniques. The drama not only tells the story of an intense familial conflict revolving around the theme of faith rooted in the Bruneian tradition, it also implies the necessity of an internal negotiation between the predominant Islamic ideology and the increasingly secularised Bruneian civil society at the time. While the implied negotiation may have been unintended or subconscious in the original making of the film, it is well-balanced and reflective of the political and social reality of Brunei as a British Protectorate in the late 1960s, foreshadowing the current coexistent status quo of the dominance and sacredness of MIB and the secular popular culture in Brunei.

The novel coronavirus (COVID-19) has completely changed the landscape of the hospitality industry. The World Health Organization does not officially recommend wearing face masks in the workplace. Wearing face masks is controversial worldwide, however it has been widely adopted in Hong Kong society. Hospitality practitioners have worn face masks to work and serve customers for almost a year long, matching the duration of the COVID-19 pandemic. This paper proposes a conceptual model of face mask effects and also discusses and evaluates the effects of wearing face masks during the pandemic.

A convenience sampling method is employed to investigate hospitality operators using in-depth and focus group interviews with managers, front-line staff and customers.

The perspectives of both hospitality practitioners and customers are included in this study. The concepts of (1) invisible care, (2) sense of safety and (3) service trust have been introduced in this study. These provide valuable insights for the service industry when facing a large-scale health crisis, now and in the future.

This paper analyzes interview data collected from 35 respondents – 14 managers, 6 practitioners and 15 customers – in order to understand the critical effects of wearing face masks during the pandemic and the perspectives of both hospitality practitioners and customers.

For the hospitality industry, wearing face mask in service has already become a “new normal”, face mask effects might create an impact on service design, service delivery and service quality.

The findings show that wearing face masks turns hygiene and safety into a form of invisible care in the Asian hospitality industry. Practitioners' perspective regarding the necessity of a smile is less important to Asian customers, showing a discrepancy between the two parties. Customers do not believe that service quality has dropped due to the wearing of masks, but that the level of hygiene has risen. Unlike customers, practitioners are more concerned about not providing good quality service. However, the interview data show that respondents generally agree that mask wearing is a gesture and symbol for the hospitality industry to make tangible a new form of caring, professionalism, safety concern and communication.

This study aims to examine humans’ reactions to service robots’ display of warmth in robot-to-robot interactions – a setting in which humans’ impressions of a service robot will not only be based on what this robot does in relation to humans, but also on what it does to other robots.

Service robot display of warmth was manipulated in an experimental setting in such a way that a service robot A expressed low versus high levels of warmth in relation to another service robot B.

The results indicate that a high level of warmth expressed by robot A vis-à-vis robot B boosted humans’ overall evaluations of A, and that this influence was mediated by the perceived humanness and the perceived happiness of A.

Numerous studies have examined humans’ reactions when they interact with a service robot or other synthetic agents that provide service. Future service encounters, however, will comprise also multi-robot systems, which means that there will be many opportunities for humans to be exposed to robot-to-robot interactions. Yet, this setting has hitherto rarely been examined in the service literature.

This paper aims to expand the emerging literature on COVID-19 and the financial markets by searching for a relationship between the uncertainty of the first phase of the COVID-19 pandemic experienced through social media and the extreme volatility of the Italian stock market.

The authors analyze the relationship between social media and stock market trends during the first phase of the COVID-19 pandemic through the lens of social theory and Baudrillard's simulacra and hyperreality theory. The authors conducted the data analysis in two phases: the emotional and Granger correlation analysis by using the KPI6 software to analyze 3,275,588 tweets for the predominant emotion on each day and observe its relationship with the stock market.

The research results show a significant Granger causality relation between tweets on a particular day and the closing price of the FTSE MIB during the first phase of the COVID-19 epidemic. The results highlight a strong relationship between social media hyperreality and the real world. The study confirms the role of social media in predicting stock market volatility.

The findings have theoretical and practical implications as they reveal the relevance of social media in our society and its relationship with businesses and economies. In an emergency, social media, as an expression of users' feelings and emotions, can generate a state of hyperreality that is strong correlated with reality. Since social media allows users to publish and share messages without any filter and mediation, the hyperreality generated is affected by highly subjective elements.

This research is different from the previous ones on the same topic because unlike previous studies, conducted under normal or simulated scenarios, this study is focused on the first phase of an unpredictable and unforeseen emergency event: the COVID-19 pandemic. This research adopts a multidisciplinary approach and integrates previous studies on the economic and financial effects generated by social media by applying well-known theories to a new and unexplored context. The study reveals the significant impact generated by social media on stock markets during a global pandemic.