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In many security domains, the ‘human in the system’ is often a critical line of defence in identifying, preventing and responding to any threats (Saikayasit, Stedmon, & Lawson, 2015). Traditionally, such security domains are often focussed on mainstream public safety within crowded spaces and border controls, through to identifying suspicious behaviours, hostile reconnaissance and implementing counter-terrorism initiatives. More recently, with growing insecurity around the world, organisations have looked to improve their security risk management frameworks, developing concepts which originated in the health and safety field to deal with more pressing risks such as terrorist acts, abduction and piracy (Paul, 2018). In these instances, security is usually the specific responsibility of frontline personnel with defined roles and responsibilities operating in accordance with organisational protocols (Saikayasit, Stedmon, Lawson, & Fussey, 2012; Stedmon, Saikayasit, Lawson, & Fussey, 2013). However, understanding the knowledge that frontline security workers might possess and use requires sensitive investigation in equally sensitive security domains.

This chapter considers how to investigate knowledge elicitation in these sensitive security domains and underlying ethics in research design that supports and protects the nature of investigation and end-users alike. This chapter also discusses the criteria used for ensuring trustworthiness as well as assessing the relative merits of the range of methods adopted.

Studying abroad is not new for Hong Kong students, especially those from the middle class. For a variety of reasons, traversing to Mainland universities has been an unconventional path confined mostly to students who pursued specific programs, or had family or social ties. Beginning in 2012, an admission scheme was launched for Hong Kong students applying to Mainland universities. The purpose of this paper is to review the admission scheme.

This paper draws on both quantitative and qualitative data sources. It includes statistics from official records of students’ application and enrollment figures, and documents obtained from multiple sources, as well as qualitative data through interviews of Hong Kong students who are studying in the Mainland universities.

The key findings are that since the implementation of the admission scheme, the number of applicants is rather stable irrespective of the changing socio-economic and political context. With the preferential treatment for Hong Kong students, low tuition fees, government financial assistance and scholarships, most students still consider studying in the Mainland a backup plan rather than a first choice. The academic performance of the students and academic/career aspirations have influenced their choice and decisions.

This paper contributes through providing both primary and secondary data to help understand the level of acceptance on the scheme since its implementation. It also reveals the perceptions of the students who have made their choice to study cross the border. In facing the emergent economic, socio-cultural and political challenges, some policies recommendations are proposed to boost the acceptance of the scheme. Moreover, it fills the research gap on student mobility from Hong Kong to Mainland China in the corpus of literature.

FDI is considered to be a meaningful component for the economic growth of a country. But, it has not been proven clear that the effect of FDI is really beneficial in a host country regardless of the state of the countries. This paper tries to provide an evidence of the effect of FDI in developing country. To do this, we relate industry level value-added to inward and outward FDI stocks in Korea in a production function framework. Especially we divide inward FDI into FDI on the Greenfield projects and FDI for M&A. The results show that the effect of inward FDI as a whole on productivity is not statistically significant, though we can presume that the direction is positive, whereas the effect of outward FDI is strongly negative, and is statistically significant. But the effects of inward FDI by the characteristics of FDI are not differentiated.

Aircraft availability (AA) is a key metric for assessing operational readiness. The declining trend in AA is a documented concern for senior Air Force leaders. This paper aims to investigate the components of non-available time and subsequently focuses on the largest and fastest growing category: not mission capable maintenance unscheduled (NMCMU). Then, utilization of aircraft platforms is examined to determine the readiness benefits of increasing available hours.

Stepwise regression is conducted on a data set of 30 aircraft platforms, consisting of 542 observations from 1998 to 2017, to reveal drivers of NMCMU. Next, utilization of aircraft platforms is examined through regression and correlation analysis of aircraft platforms and sorties or hours flown.

Regression analysis reveals drivers of NMCMU include platform type, average age of aircraft, fleet size, breaks and cannibalization. These factors explain 80.6 per cent of the variance in the data set when predicting NMCMU. Additionally, the utilization results show that when more hours are made available, 5 per cent of each new hour is used for flying. Further analysis at the individual platform level finds a strong or moderate correlation between available hours and sorties flown for 93 per cent of the platforms.

Implications from the regression analysis demonstrate there are remedies to increase AA, but many of these remedies may be costly. The utilization analysis expresses the potential readiness benefits of increasing available hours.

The purpose of this paper is to evaluate innovations in intellectual property rights (IPR) databases, techniques and software tools, with an emphasis on selected new developments and their contribution towards achieving advantages for IPR management (IPRM) and wider social benefits. Several industry buzzwords are addressed, such as IPR-linked open data (IPR LOD) databases, blockchain and IPR-related techniques, acknowledged for their contribution in moving towards artificial intelligence (AI) in IPRM.

The evaluation, following an original framework developed by the authors, is based on a literature review, web analysis and interviews carried out with some of the top experts from IPR-savvy multinational companies.

The paper presents the patent databases landscape, classifying patent offices according to the format of data provided and depicting the state-of-art in the IPR LOD. An examination of existing IPR tools shows that they are not yet fully developed, with limited usability for IPRM. After reviewing the techniques, it is clear that the current state-of-the-art is insufficient to fully address AI in IPR. Uses of blockchain in IPR show that they are yet to be fully exploited on a larger scale.

A critical analysis of IPR tools, techniques and blockchain allows for the state-of-art to be assessed, and for their current and potential value with regard to the development of the economy and wider society to be considered. The paper also provides a novel classification of patent offices and an original IPR-linked open data landscape.